Upregulated expression of La ribonucleoprotein domain family member 6 and collagen type I gene following water-filtered broad-spectrum near-infrared irradiation in a 3-dimensional human epidermal tissue culture model as revealed by microarray analysis.

PubMed

Tanaka, Yohei; Nakayama, Jun

2018-05-01

Water-filtered broad-spectrum near-infrared irradiation can induce various biological effects, as our previous clinical, histological, and biochemical investigations have shown. However, few studies that examined the changes thus induced in gene expression. The aim was to investigate the changes in gene expression in a 3-dimensional reconstructed epidermal tissue culture exposed to water-filtered broad-spectrum near-infrared irradiation. DNA microarray and quantitative real-time polymerase chain reaction (PCR) analysis was used to assess gene expression levels in a 3-dimensional reconstructed epidermal model composed of normal human epidermal cells exposed to water-filtered broad-spectrum near-infrared irradiation. The water filter allowed 1000-1800 nm wavelengths and excluded 1400-1500 nm wavelengths, and cells were exposed to 5 or 10 rounds of near-infrared irradiation at 10 J/cm 2 . A DNA microarray with over 50 000 different probes showed 18 genes that were upregulated or downregulated by at least twofold after irradiation. Quantitative real-time PCR revealed that, relative to control cells, the gene encoding La ribonucleoprotein domain family member 6 (LARP6), which regulates collagen expression, was significantly and dose-dependently upregulated (P < 0.05) by water-filtered broad-spectrum near-infrared exposure. Gene encoding transcripts of collagen type I were significantly upregulated compared with controls (P < 0.05). This study demonstrates the ability of water-filtered broad-spectrum near-infrared irradiation to stimulate the production of type I collagen. © 2017 The Australasian College of Dermatologists.

Dimensionality of Data Matrices with Applications to Gene Expression Profiles

ERIC Educational Resources Information Center

Feng, Xingdong

2009-01-01

Probe-level microarray data are usually stored in matrices. Take a given probe set (gene), for example, each row of the matrix corresponds to an array, and each column corresponds to a probe. Often, people summarize each array by the gene expression level. Is one number sufficient to summarize a whole probe set for a specific gene in an array?…

A Java tool for dynamic web-based 3D visualization of anatomy and overlapping gene or protein expression patterns.

PubMed

Gerth, Victor E; Vize, Peter D

2005-04-01

The Gene Expression Viewer is a web-launched three-dimensional visualization tool, tailored to compare surface reconstructions of multi-channel image volumes generated by confocal microscopy or micro-CT.

Prediction of epigenetically regulated genes in breast cancer cell lines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Loss, Leandro A; Sadanandam, Anguraj; Durinck, Steffen

Methylation of CpG islands within the DNA promoter regions is one mechanism that leads to aberrant gene expression in cancer. In particular, the abnormal methylation of CpG islands may silence associated genes. Therefore, using high-throughput microarrays to measure CpG island methylation will lead to better understanding of tumor pathobiology and progression, while revealing potentially new biomarkers. We have examined a recently developed high-throughput technology for measuring genome-wide methylation patterns called mTACL. Here, we propose a computational pipeline for integrating gene expression and CpG island methylation profles to identify epigenetically regulated genes for a panel of 45 breast cancer cell lines,more » which is widely used in the Integrative Cancer Biology Program (ICBP). The pipeline (i) reduces the dimensionality of the methylation data, (ii) associates the reduced methylation data with gene expression data, and (iii) ranks methylation-expression associations according to their epigenetic regulation. Dimensionality reduction is performed in two steps: (i) methylation sites are grouped across the genome to identify regions of interest, and (ii) methylation profles are clustered within each region. Associations between the clustered methylation and the gene expression data sets generate candidate matches within a fxed neighborhood around each gene. Finally, the methylation-expression associations are ranked through a logistic regression, and their significance is quantified through permutation analysis. Our two-step dimensionality reduction compressed 90% of the original data, reducing 137,688 methylation sites to 14,505 clusters. Methylation-expression associations produced 18,312 correspondences, which were used to further analyze epigenetic regulation. Logistic regression was used to identify 58 genes from these correspondences that showed a statistically signifcant negative correlation between methylation profles and gene expression in the panel of breast cancer cell lines. Subnetwork enrichment of these genes has identifed 35 common regulators with 6 or more predicted markers. In addition to identifying epigenetically regulated genes, we show evidence of differentially expressed methylation patterns between the basal and luminal subtypes. Our results indicate that the proposed computational protocol is a viable platform for identifying epigenetically regulated genes. Our protocol has generated a list of predictors including COL1A2, TOP2A, TFF1, and VAV3, genes whose key roles in epigenetic regulation is documented in the literature. Subnetwork enrichment of these predicted markers further suggests that epigenetic regulation of individual genes occurs in a coordinated fashion and through common regulators.« less

Cell Fate Decision as High-Dimensional Critical State Transition

PubMed Central

Zhou, Joseph; Castaño, Ivan G.; Leong-Quong, Rebecca Y. Y.; Chang, Hannah; Trachana, Kalliopi; Giuliani, Alessandro; Huang, Sui

2016-01-01

Cell fate choice and commitment of multipotent progenitor cells to a differentiated lineage requires broad changes of their gene expression profile. But how progenitor cells overcome the stability of their gene expression configuration (attractor) to exit the attractor in one direction remains elusive. Here we show that commitment of blood progenitor cells to the erythroid or myeloid lineage is preceded by the destabilization of their high-dimensional attractor state, such that differentiating cells undergo a critical state transition. Single-cell resolution analysis of gene expression in populations of differentiating cells affords a new quantitative index for predicting critical transitions in a high-dimensional state space based on decrease of correlation between cells and concomitant increase of correlation between genes as cells approach a tipping point. The detection of “rebellious cells” that enter the fate opposite to the one intended corroborates the model of preceding destabilization of a progenitor attractor. Thus, early warning signals associated with critical transitions can be detected in statistical ensembles of high-dimensional systems, offering a formal theory-based approach for analyzing single-cell molecular profiles that goes beyond current computational pattern recognition, does not require knowledge of specific pathways, and could be used to predict impending major shifts in development and disease. PMID:28027308

Quantification of HSV-1-mediated expression of the ferritin MRI reporter in the mouse brain

PubMed Central

Iordanova, B; Goins, WF; Clawson, DS; Hitchens, TK; Ahrens, ET

2017-01-01

The development of effective strategies for gene therapy has been hampered by difficulties verifying transgene delivery in vivo and quantifying gene expression non-invasively. Magnetic resonance imaging (MRI) offers high spatial resolution and three-dimensional views, without tissue depth limitations. The iron-storage protein ferritin is a prototype MRI gene reporter. Ferritin forms a paramagnetic ferrihydrite core that can be detected by MRI via its effect on the local magnetic field experienced by water protons. In an effort to better characterize the ferritin reporter for central nervous system applications, we expressed ferritin in the mouse brain in vivo using a neurotropic herpes simplex virus type 1 (HSV-1). We computed three-dimensional maps of MRI transverse relaxation rates in the mouse brain with ascending doses of ferritin-expressing HSV-1. We established that the transverse relaxation rates correlate significantly to the number of inoculated infectious particles. Our results are potentially useful for quantitatively assessing limitations of ferritin reporters for gene therapy applications. PMID:22996196

Case-based retrieval framework for gene expression data.

PubMed

Anaissi, Ali; Goyal, Madhu; Catchpoole, Daniel R; Braytee, Ali; Kennedy, Paul J

2015-01-01

The process of retrieving similar cases in a case-based reasoning system is considered a big challenge for gene expression data sets. The huge number of gene expression values generated by microarray technology leads to complex data sets and similarity measures for high-dimensional data are problematic. Hence, gene expression similarity measurements require numerous machine-learning and data-mining techniques, such as feature selection and dimensionality reduction, to be incorporated into the retrieval process. This article proposes a case-based retrieval framework that uses a k-nearest-neighbor classifier with a weighted-feature-based similarity to retrieve previously treated patients based on their gene expression profiles. The herein-proposed methodology is validated on several data sets: a childhood leukemia data set collected from The Children's Hospital at Westmead, as well as the Colon cancer, the National Cancer Institute (NCI), and the Prostate cancer data sets. Results obtained by the proposed framework in retrieving patients of the data sets who are similar to new patients are as follows: 96% accuracy on the childhood leukemia data set, 95% on the NCI data set, 93% on the Colon cancer data set, and 98% on the Prostate cancer data set. The designed case-based retrieval framework is an appropriate choice for retrieving previous patients who are similar to a new patient, on the basis of their gene expression data, for better diagnosis and treatment of childhood leukemia. Moreover, this framework can be applied to other gene expression data sets using some or all of its steps.

Computational gene expression profiling under salt stress reveals patterns of co-expression

PubMed Central

Sanchita; Sharma, Ashok

2016-01-01

Plants respond differently to environmental conditions. Among various abiotic stresses, salt stress is a condition where excess salt in soil causes inhibition of plant growth. To understand the response of plants to the stress conditions, identification of the responsible genes is required. Clustering is a data mining technique used to group the genes with similar expression. The genes of a cluster show similar expression and function. We applied clustering algorithms on gene expression data of Solanum tuberosum showing differential expression in Capsicum annuum under salt stress. The clusters, which were common in multiple algorithms were taken further for analysis. Principal component analysis (PCA) further validated the findings of other cluster algorithms by visualizing their clusters in three-dimensional space. Functional annotation results revealed that most of the genes were involved in stress related responses. Our findings suggest that these algorithms may be helpful in the prediction of the function of co-expressed genes. PMID:26981411

Robust and sparse correlation matrix estimation for the analysis of high-dimensional genomics data.

PubMed

Serra, Angela; Coretto, Pietro; Fratello, Michele; Tagliaferri, Roberto; Stegle, Oliver

2018-02-15

Microarray technology can be used to study the expression of thousands of genes across a number of different experimental conditions, usually hundreds. The underlying principle is that genes sharing similar expression patterns, across different samples, can be part of the same co-expression system, or they may share the same biological functions. Groups of genes are usually identified based on cluster analysis. Clustering methods rely on the similarity matrix between genes. A common choice to measure similarity is to compute the sample correlation matrix. Dimensionality reduction is another popular data analysis task which is also based on covariance/correlation matrix estimates. Unfortunately, covariance/correlation matrix estimation suffers from the intrinsic noise present in high-dimensional data. Sources of noise are: sampling variations, presents of outlying sample units, and the fact that in most cases the number of units is much larger than the number of genes. In this paper, we propose a robust correlation matrix estimator that is regularized based on adaptive thresholding. The resulting method jointly tames the effects of the high-dimensionality, and data contamination. Computations are easy to implement and do not require hand tunings. Both simulated and real data are analyzed. A Monte Carlo experiment shows that the proposed method is capable of remarkable performances. Our correlation metric is more robust to outliers compared with the existing alternatives in two gene expression datasets. It is also shown how the regularization allows to automatically detect and filter spurious correlations. The same regularization is also extended to other less robust correlation measures. Finally, we apply the ARACNE algorithm on the SyNTreN gene expression data. Sensitivity and specificity of the reconstructed network is compared with the gold standard. We show that ARACNE performs better when it takes the proposed correlation matrix estimator as input. The R software is available at https://github.com/angy89/RobustSparseCorrelation. aserra@unisa.it or robtag@unisa.it. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Novel regulatory loci controlling oxygen- and pH-regulated gene expression in Salmonella typhimurium.

PubMed Central

Aliabadi, Z; Park, Y K; Slonczewski, J L; Foster, J W

1988-01-01

Three new loci were discovered, each of which participates in the regulation of anaerobic gene expression. The regulatory gene earA negatively regulates the expression of the anaerobiosis-inducible gene aniG as well as that of at least three other genes, as determined by two-dimensional polyacrylamide gel electrophoresis. The earA locus maps at 86 min. The expression of aniG was also shown to be controlled by changes in external pH under aerobic and anaerobic conditions. Maximal expression was observed under anaerobic conditions at an external pH of 6.0. Significant transcriptional activity was also observed under aerobic conditions at pH 6.0. This was in contrast to hyd, whose expression was dependent upon anaerobiosis and varied with external pH. The pH dependence disappeared under fully aerobic conditions. Mutations in earA had no effect upon hyd expression. The two other regulators identified were oxrF, which controls aniH, and oxrG, which, in concert with oxrA and oxrB, controls aniC and aniI. The oxrG locus was mapped to 88 min and appears to code for a positive regulator. Various oxr mutants were subjected to two-dimensional polyacrylamide electrophoretic analysis of anaerobiosis-inducible proteins. Several pathways of anaerobic control were observed by means of these techniques. Images PMID:3276666

A combinatorial code for pattern formation in Drosophila oogenesis.

PubMed

Yakoby, Nir; Bristow, Christopher A; Gong, Danielle; Schafer, Xenia; Lembong, Jessica; Zartman, Jeremiah J; Halfon, Marc S; Schüpbach, Trudi; Shvartsman, Stanislav Y

2008-11-01

Two-dimensional patterning of the follicular epithelium in Drosophila oogenesis is required for the formation of three-dimensional eggshell structures. Our analysis of a large number of published gene expression patterns in the follicle cells suggests that they follow a simple combinatorial code based on six spatial building blocks and the operations of union, difference, intersection, and addition. The building blocks are related to the distribution of inductive signals, provided by the highly conserved epidermal growth factor receptor and bone morphogenetic protein signaling pathways. We demonstrate the validity of the code by testing it against a set of patterns obtained in a large-scale transcriptional profiling experiment. Using the proposed code, we distinguish 36 distinct patterns for 81 genes expressed in the follicular epithelium and characterize their joint dynamics over four stages of oogenesis. The proposed combinatorial framework allows systematic analysis of the diversity and dynamics of two-dimensional transcriptional patterns and guides future studies of gene regulation.

Multivariate Boosting for Integrative Analysis of High-Dimensional Cancer Genomic Data

PubMed Central

Xiong, Lie; Kuan, Pei-Fen; Tian, Jianan; Keles, Sunduz; Wang, Sijian

2015-01-01

In this paper, we propose a novel multivariate component-wise boosting method for fitting multivariate response regression models under the high-dimension, low sample size setting. Our method is motivated by modeling the association among different biological molecules based on multiple types of high-dimensional genomic data. Particularly, we are interested in two applications: studying the influence of DNA copy number alterations on RNA transcript levels and investigating the association between DNA methylation and gene expression. For this purpose, we model the dependence of the RNA expression levels on DNA copy number alterations and the dependence of gene expression on DNA methylation through multivariate regression models and utilize boosting-type method to handle the high dimensionality as well as model the possible nonlinear associations. The performance of the proposed method is demonstrated through simulation studies. Finally, our multivariate boosting method is applied to two breast cancer studies. PMID:26609213

Embryonic Wnt gene expression in the nitrofen-induced hypoplastic lung using 3-dimensional imaging.

PubMed

Takayasu, Hajime; Murphy, Paula; Sato, Hideaki; Doi, Takashi; Puri, Prem

2010-11-01

Wnts have been reported to play a key role in the lung morphogenesis. We have previously reported that pulmonary gene expression of Wnt2 and Wnt7b is downregulated on day 15 of gestation in the nitrofen-induced congenital diaphragmatic hernia (CDH) model. However, the distribution pattern of gene expression of Wnts in the very early lung development remains unclear. Optical projection tomography (OPT) is a new technique for 3-dimensional imaging of small developing organs and gene distribution combined with whole-mount in situ hybridization. We designed this study to investigate the distribution pattern of Wnts gene expression in lung buds of nitrofen-induced CDH model using OPT. Embryos from normal and nitrofen-treated dams were harvested on embryonic day 10 (E10), and divided into controls and nitrofen group, respectively. Whole-mount in situ hybridization to detect transcripts of Wnt2 and Wnt7b was performed, analyzed, and reconstructed using OPT. The expression of Wnt2 transcripts was detected in the lung bud mesenchyme and markedly diminished in nitrofen group compared to controls, whereas Wnt7b transcripts were expressed in the mesoderm of bronchi and the lung bud with no detectable difference between 2 groups. We provide evidence for the first time that Wnt2 expression is downregulated at lung bud stage in the nitrofen model. Optical projection tomography is potentially a useful approach to visualize both gene expression and morphology during very early stages of lung development. Copyright © 2010 Elsevier Inc. All rights reserved.

A 3-dimensional human embryonic stem cell (hESC)-derived model to detect developmental neurotoxicity of nanoparticles.

PubMed

Hoelting, Lisa; Scheinhardt, Benjamin; Bondarenko, Olesja; Schildknecht, Stefan; Kapitza, Marion; Tanavde, Vivek; Tan, Betty; Lee, Qian Yi; Mecking, Stefan; Leist, Marcel; Kadereit, Suzanne

2013-04-01

Nanoparticles (NPs) have been shown to accumulate in organs, cross the blood-brain barrier and placenta, and have the potential to elicit developmental neurotoxicity (DNT). Here, we developed a human embryonic stem cell (hESC)-derived 3-dimensional (3-D) in vitro model that allows for testing of potential developmental neurotoxicants. Early central nervous system PAX6(+) precursor cells were generated from hESCs and differentiated further within 3-D structures. The 3-D model was characterized for neural marker expression revealing robust differentiation toward neuronal precursor cells, and gene expression profiling suggested a predominantly forebrain-like development. Altered neural gene expression due to exposure to non-cytotoxic concentrations of the known developmental neurotoxicant, methylmercury, indicated that the 3-D model could detect DNT. To test for specific toxicity of NPs, chemically inert polyethylene NPs (PE-NPs) were chosen. They penetrated deep into the 3-D structures and impacted gene expression at non-cytotoxic concentrations. NOTCH pathway genes such as HES5 and NOTCH1 were reduced in expression, as well as downstream neuronal precursor genes such as NEUROD1 and ASCL1. FOXG1, a patterning marker, was also reduced. As loss of function of these genes results in severe nervous system impairments in mice, our data suggest that the 3-D hESC-derived model could be used to test for Nano-DNT.

A genome-scale map of expression for a mouse brain section obtained using voxelation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chin, Mark H.; Geng, Alex B.; Khan, Arshad H.

Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological diseases. We have reconstructed 2- dimensional images of gene expression for 20,000 genes in a coronal slice of the mouse brain at the level of the striatum by using microarrays in combination with voxelation at a resolution of 1 mm3. Good reliability of the microarray results were confirmed using multiple replicates, subsequent quantitative RT-PCR voxelation, mass spectrometry voxelation and publicly available in situ hybridization data. Known and novel genes were identified with expression patterns localized to defined substructures within the brain. In addition, genesmore » with unexpected patterns were identified and cluster analysis identified a set of genes with a gradient of dorsal/ventral expression not restricted to known anatomical boundaries. The genome-scale maps of gene expression obtained using voxelation will be a valuable tool for the neuroscience community.« less

Role of fruA and csgA genes in gene expression during development of Myxococcus xanthus. Analysis by two-dimensional gel electrophoresis.

PubMed

Horiuchi, Takayuki; Taoka, Masato; Isobe, Toshiaki; Komano, Teruya; Inouye, Sumiko

2002-07-26

Two genes, fruA and csgA, encoding a putative transcription factor and C-factor, respectively, are essential for fruiting body formation of Myxococcus xanthus. To investigate the role of fruA and csgA genes in developmental gene expression, developing cells as well as vegetative cells of M. xanthus wild-type, fruA::Tc, and csgA731 strains were pulse-labeled with [(35)S]methionine, and the whole cell proteins were analyzed using two-dimensional immobilized pH gradient/SDS-PAGE. Differences in protein synthesis patterns among more than 700 protein spots were detected during development of the three strains. Fourteen proteins showing distinctly different expression patterns in mutant cells were analyzed in more detail. Five of the 14 proteins were identified as elongation factor Tu (EF-Tu), Dru, DofA, FruA, and protein S by immunoblot analysis and mass spectroscopy. A gene encoding DofA was cloned and sequenced. Although both fruA and csgA genes regulate early development of M. xanthus, they were found to differently regulate expression of several developmental genes. The production of six proteins, including DofA and protein S, was dependent on fruA, whereas the production of two proteins was dependent on csgA, and one protein was dependent on both fruA and csgA. To explain the present findings, a new model was presented in which different levels of FruA phosphorylation may distinctively regulate the expression of two groups of developmental genes.

The PEPR GeneChip data warehouse, and implementation of a dynamic time series query tool (SGQT) with graphical interface.

PubMed

Chen, Josephine; Zhao, Po; Massaro, Donald; Clerch, Linda B; Almon, Richard R; DuBois, Debra C; Jusko, William J; Hoffman, Eric P

2004-01-01

Publicly accessible DNA databases (genome browsers) are rapidly accelerating post-genomic research (see http://www.genome.ucsc.edu/), with integrated genomic DNA, gene structure, EST/ splicing and cross-species ortholog data. DNA databases have relatively low dimensionality; the genome is a linear code that anchors all associated data. In contrast, RNA expression and protein databases need to be able to handle very high dimensional data, with time, tissue, cell type and genes, as interrelated variables. The high dimensionality of microarray expression profile data, and the lack of a standard experimental platform have complicated the development of web-accessible databases and analytical tools. We have designed and implemented a public resource of expression profile data containing 1024 human, mouse and rat Affymetrix GeneChip expression profiles, generated in the same laboratory, and subject to the same quality and procedural controls (Public Expression Profiling Resource; PEPR). Our Oracle-based PEPR data warehouse includes a novel time series query analysis tool (SGQT), enabling dynamic generation of graphs and spreadsheets showing the action of any transcript of interest over time. In this report, we demonstrate the utility of this tool using a 27 time point, in vivo muscle regeneration series. This data warehouse and associated analysis tools provides access to multidimensional microarray data through web-based interfaces, both for download of all types of raw data for independent analysis, and also for straightforward gene-based queries. Planned implementations of PEPR will include web-based remote entry of projects adhering to quality control and standard operating procedure (QC/SOP) criteria, and automated output of alternative probe set algorithms for each project (see http://microarray.cnmcresearch.org/pgadatatable.asp).

The PEPR GeneChip data warehouse, and implementation of a dynamic time series query tool (SGQT) with graphical interface

PubMed Central

Chen, Josephine; Zhao, Po; Massaro, Donald; Clerch, Linda B.; Almon, Richard R.; DuBois, Debra C.; Jusko, William J.; Hoffman, Eric P.

2004-01-01

Publicly accessible DNA databases (genome browsers) are rapidly accelerating post-genomic research (see http://www.genome.ucsc.edu/), with integrated genomic DNA, gene structure, EST/ splicing and cross-species ortholog data. DNA databases have relatively low dimensionality; the genome is a linear code that anchors all associated data. In contrast, RNA expression and protein databases need to be able to handle very high dimensional data, with time, tissue, cell type and genes, as interrelated variables. The high dimensionality of microarray expression profile data, and the lack of a standard experimental platform have complicated the development of web-accessible databases and analytical tools. We have designed and implemented a public resource of expression profile data containing 1024 human, mouse and rat Affymetrix GeneChip expression profiles, generated in the same laboratory, and subject to the same quality and procedural controls (Public Expression Profiling Resource; PEPR). Our Oracle-based PEPR data warehouse includes a novel time series query analysis tool (SGQT), enabling dynamic generation of graphs and spreadsheets showing the action of any transcript of interest over time. In this report, we demonstrate the utility of this tool using a 27 time point, in vivo muscle regeneration series. This data warehouse and associated analysis tools provides access to multidimensional microarray data through web-based interfaces, both for download of all types of raw data for independent analysis, and also for straightforward gene-based queries. Planned implementations of PEPR will include web-based remote entry of projects adhering to quality control and standard operating procedure (QC/SOP) criteria, and automated output of alternative probe set algorithms for each project (see http://microarray.cnmcresearch.org/pgadatatable.asp). PMID:14681485

Building quantitative, three-dimensional atlases of gene expression and morphology at cellular resolution.

PubMed

Knowles, David W; Biggin, Mark D

2013-01-01

Animals comprise dynamic three-dimensional arrays of cells that express gene products in intricate spatial and temporal patterns that determine cellular differentiation and morphogenesis. A rigorous understanding of these developmental processes requires automated methods that quantitatively record and analyze complex morphologies and their associated patterns of gene expression at cellular resolution. Here we summarize light microscopy-based approaches to establish permanent, quantitative datasets-atlases-that record this information. We focus on experiments that capture data for whole embryos or large areas of tissue in three dimensions, often at multiple time points. We compare and contrast the advantages and limitations of different methods and highlight some of the discoveries made. We emphasize the need for interdisciplinary collaborations and integrated experimental pipelines that link sample preparation, image acquisition, image analysis, database design, visualization, and quantitative analysis. Copyright © 2013 Wiley Periodicals, Inc.

Discovering biclusters in gene expression data based on high-dimensional linear geometries

PubMed Central

Gan, Xiangchao; Liew, Alan Wee-Chung; Yan, Hong

2008-01-01

Background In DNA microarray experiments, discovering groups of genes that share similar transcriptional characteristics is instrumental in functional annotation, tissue classification and motif identification. However, in many situations a subset of genes only exhibits consistent pattern over a subset of conditions. Conventional clustering algorithms that deal with the entire row or column in an expression matrix would therefore fail to detect these useful patterns in the data. Recently, biclustering has been proposed to detect a subset of genes exhibiting consistent pattern over a subset of conditions. However, most existing biclustering algorithms are based on searching for sub-matrices within a data matrix by optimizing certain heuristically defined merit functions. Moreover, most of these algorithms can only detect a restricted set of bicluster patterns. Results In this paper, we present a novel geometric perspective for the biclustering problem. The biclustering process is interpreted as the detection of linear geometries in a high dimensional data space. Such a new perspective views biclusters with different patterns as hyperplanes in a high dimensional space, and allows us to handle different types of linear patterns simultaneously by matching a specific set of linear geometries. This geometric viewpoint also inspires us to propose a generic bicluster pattern, i.e. the linear coherent model that unifies the seemingly incompatible additive and multiplicative bicluster models. As a particular realization of our framework, we have implemented a Hough transform-based hyperplane detection algorithm. The experimental results on human lymphoma gene expression dataset show that our algorithm can find biologically significant subsets of genes. Conclusion We have proposed a novel geometric interpretation of the biclustering problem. We have shown that many common types of bicluster are just different spatial arrangements of hyperplanes in a high dimensional data space. An implementation of the geometric framework using the Fast Hough transform for hyperplane detection can be used to discover biologically significant subsets of genes under subsets of conditions for microarray data analysis. PMID:18433477

3D chromosome rendering from Hi-C data using virtual reality

NASA Astrophysics Data System (ADS)

Zhu, Yixin; Selvaraj, Siddarth; Weber, Philip; Fang, Jennifer; Schulze, Jürgen P.; Ren, Bing

2015-01-01

Most genome browsers display DNA linearly, using single-dimensional depictions that are useful to examine certain epigenetic mechanisms such as DNA methylation. However, these representations are insufficient to visualize intrachromosomal interactions and relationships between distal genome features. Relationships between DNA regions may be difficult to decipher or missed entirely if those regions are distant in one dimension but could be spatially proximal when mapped to three-dimensional space. For example, the visualization of enhancers folding over genes is only fully expressed in three-dimensional space. Thus, to accurately understand DNA behavior during gene expression, a means to model chromosomes is essential. Using coordinates generated from Hi-C interaction frequency data, we have created interactive 3D models of whole chromosome structures and its respective domains. We have also rendered information on genomic features such as genes, CTCF binding sites, and enhancers. The goal of this article is to present the procedure, findings, and conclusions of our models and renderings.

Drug transporter expression profiling in a three-dimensional kidney proximal tubule in vitro nephrotoxicity model.

PubMed

Diekjürgen, Dorina; Grainger, David W

2018-05-09

Given currently poor toxicity translational predictions for drug candidates, improved mechanistic understanding underlying nephrotoxicity and drug renal clearance is needed to improve drug development and safety screening. Therefore, better relevant and well-characterized in vitro screening models are required to reliably predict human nephrotoxicity. Because kidney proximal tubules are central to active drug uptake and secretion processes and therefore to nephrotoxicity, this study acquired regio-specific expression data from recently reported primary proximal tubule three-dimensional (3D) hyaluronic acid gel culture and non-gel embedded cultured murine proximal tubule suspensions used in nephrotoxicity assays. Quantitative assessment of the mRNA expression of 21 known kidney tubule markers and important proximal tubule transporters with known roles in drug transport was obtained. Asserting superior gene expression levels over current commonly used two-dimensional (2D) kidney cell culture lines was the study objective. Hence, we compare previously published gel-based 3D proximal tubule fragment culture and their non-gel suspensions for up to 1 week. We demonstrate that 3D tubule culture exhibits superior gene expression levels and profiles compared to published commonly used 2D kidney cell lines (Caki-1 and HK-2) in plastic plate monocultures. Additionally, nearly all tested genes retain mRNA expression after 7 days in both proximal tubule cultures, a limitation of 2D cell culture lines. Importantly, gel presence is shown not to interfere with the gene expression assay. Western blots confirm protein expression of OAT1 and 3 and OCT2. Functional transport assays confirm their respective transporter functions in vitro. Overall, results validate retention of essential toxicity-relevant transporters in this published 3D proximal tubule model over conventional 2D kidney cell cultures, producing opportunities for more reliable, sensitive, and comprehensive drug toxicity studies relevant to drug development and nephrotoxicity goals.

ExAtlas: An interactive online tool for meta-analysis of gene expression data.

PubMed

Sharov, Alexei A; Schlessinger, David; Ko, Minoru S H

2015-12-01

We have developed ExAtlas, an on-line software tool for meta-analysis and visualization of gene expression data. In contrast to existing software tools, ExAtlas compares multi-component data sets and generates results for all combinations (e.g. all gene expression profiles versus all Gene Ontology annotations). ExAtlas handles both users' own data and data extracted semi-automatically from the public repository (GEO/NCBI database). ExAtlas provides a variety of tools for meta-analyses: (1) standard meta-analysis (fixed effects, random effects, z-score, and Fisher's methods); (2) analyses of global correlations between gene expression data sets; (3) gene set enrichment; (4) gene set overlap; (5) gene association by expression profile; (6) gene specificity; and (7) statistical analysis (ANOVA, pairwise comparison, and PCA). ExAtlas produces graphical outputs, including heatmaps, scatter-plots, bar-charts, and three-dimensional images. Some of the most widely used public data sets (e.g. GNF/BioGPS, Gene Ontology, KEGG, GAD phenotypes, BrainScan, ENCODE ChIP-seq, and protein-protein interaction) are pre-loaded and can be used for functional annotations.

Fractal Clustering and Knowledge-driven Validation Assessment for Gene Expression Profiling.

PubMed

Wang, Lu-Yong; Balasubramanian, Ammaiappan; Chakraborty, Amit; Comaniciu, Dorin

2005-01-01

DNA microarray experiments generate a substantial amount of information about the global gene expression. Gene expression profiles can be represented as points in multi-dimensional space. It is essential to identify relevant groups of genes in biomedical research. Clustering is helpful in pattern recognition in gene expression profiles. A number of clustering techniques have been introduced. However, these traditional methods mainly utilize shape-based assumption or some distance metric to cluster the points in multi-dimension linear Euclidean space. Their results shows poor consistence with the functional annotation of genes in previous validation study. From a novel different perspective, we propose fractal clustering method to cluster genes using intrinsic (fractal) dimension from modern geometry. This method clusters points in such a way that points in the same clusters are more self-affine among themselves than to the points in other clusters. We assess this method using annotation-based validation assessment for gene clusters. It shows that this method is superior in identifying functional related gene groups than other traditional methods.

Long-term three-dimensional perfusion culture of human adult bone marrow mononuclear cells in bioreactors.

PubMed

Schmelzer, Eva; Finoli, Anthony; Nettleship, Ian; Gerlach, Jörg C

2015-04-01

The construction and long-term maintenance of three-dimensional in vitro bone marrow models is of great interest but still quite challenging. Here we describe the use of a multi-compartment hollow-fiber membrane based three-dimensional perfusion bioreactor for long-term culture of whole human bone marrow mononuclear cells. We also investigated bioreactors with incorporated open-porous foamed hydroxyapatite scaffolds, mimicking the in vivo bone matrix. Cells in bioreactors with and without scaffolds were cultured to 6 weeks and compared to Petri dish controls. Cells were analyzed for gene expression, surface markers by flow cytometry, metabolic activity, hematopoietic potential, viability, and attachment by immunocytochemistry. Cells in bioreactors were metabolic active during long-term culture. The percentages of hematopoietic stem cell and mature endothelial cell fractions were maintained in bioreactors. The expression of most of the analyzed genes stabilized and increased after long-term culture of 6 weeks. Compared to Petri dish culture controls, bioreactor perfusion culture improved in both the short and long-term, the colony formation unit capacity of hematopoietic progenitors. Cells attached to the ample surface area provided by hydroxyapatite scaffolds. The implementation of a hydroxyapatite scaffold did not influence colony formation capacity, percentages of cell type specific fractions, gene expression, cell viability or metabolic turnover when compared to control cells cultured in bioreactors without scaffolds. In conclusion, three-dimensional perfusion bioreactor culture enables long-term maintenance of primary human bone marrow cells, with hydroxyapatite scaffolds providing an in vivo-like scaffold for three-dimensional culture. © 2015 Wiley Periodicals, Inc.

SEURAT: visual analytics for the integrated analysis of microarray data.

PubMed

Gribov, Alexander; Sill, Martin; Lück, Sonja; Rücker, Frank; Döhner, Konstanze; Bullinger, Lars; Benner, Axel; Unwin, Antony

2010-06-03

In translational cancer research, gene expression data is collected together with clinical data and genomic data arising from other chip based high throughput technologies. Software tools for the joint analysis of such high dimensional data sets together with clinical data are required. We have developed an open source software tool which provides interactive visualization capability for the integrated analysis of high-dimensional gene expression data together with associated clinical data, array CGH data and SNP array data. The different data types are organized by a comprehensive data manager. Interactive tools are provided for all graphics: heatmaps, dendrograms, barcharts, histograms, eventcharts and a chromosome browser, which displays genetic variations along the genome. All graphics are dynamic and fully linked so that any object selected in a graphic will be highlighted in all other graphics. For exploratory data analysis the software provides unsupervised data analytics like clustering, seriation algorithms and biclustering algorithms. The SEURAT software meets the growing needs of researchers to perform joint analysis of gene expression, genomical and clinical data.

Hi-C Chromatin Interaction Networks Predict Co-expression in the Mouse Cortex

PubMed Central

Hulsman, Marc; Lelieveldt, Boudewijn P. F.; de Ridder, Jeroen; Reinders, Marcel

2015-01-01

The three dimensional conformation of the genome in the cell nucleus influences important biological processes such as gene expression regulation. Recent studies have shown a strong correlation between chromatin interactions and gene co-expression. However, predicting gene co-expression from frequent long-range chromatin interactions remains challenging. We address this by characterizing the topology of the cortical chromatin interaction network using scale-aware topological measures. We demonstrate that based on these characterizations it is possible to accurately predict spatial co-expression between genes in the mouse cortex. Consistent with previous findings, we find that the chromatin interaction profile of a gene-pair is a good predictor of their spatial co-expression. However, the accuracy of the prediction can be substantially improved when chromatin interactions are described using scale-aware topological measures of the multi-resolution chromatin interaction network. We conclude that, for co-expression prediction, it is necessary to take into account different levels of chromatin interactions ranging from direct interaction between genes (i.e. small-scale) to chromatin compartment interactions (i.e. large-scale). PMID:25965262

Connected Gene Communities Underlie Transcriptional Changes in Cornelia de Lange Syndrome.

PubMed

Boudaoud, Imène; Fournier, Éric; Baguette, Audrey; Vallée, Maxime; Lamaze, Fabien C; Droit, Arnaud; Bilodeau, Steve

2017-09-01

Cornelia de Lange syndrome (CdLS) is a complex multisystem developmental disorder caused by mutations in cohesin subunits and regulators. While its precise molecular mechanisms are not well defined, they point toward a global deregulation of the transcriptional gene expression program. Cohesin is associated with the boundaries of chromosome domains and with enhancer and promoter regions connecting the three-dimensional genome organization with transcriptional regulation. Here, we show that connected gene communities, structures emerging from the interactions of noncoding regulatory elements and genes in the three-dimensional chromosomal space, provide a molecular explanation for the pathoetiology of CdLS associated with mutations in the cohesin-loading factor NIPBL and the cohesin subunit SMC1A NIPBL and cohesin are important constituents of connected gene communities that are centrally positioned at noncoding regulatory elements. Accordingly, genes deregulated in CdLS are positioned within reach of NIPBL- and cohesin-occupied regions through promoter-promoter interactions. Our findings suggest a dynamic model where NIPBL loads cohesin to connect genes in communities, offering an explanation for the gene expression deregulation in the CdLS. Copyright © 2017 by the Genetics Society of America.

CRHR1 promoter hypomethylation: An epigenetic readout of panic disorder?

PubMed

Schartner, Christoph; Ziegler, Christiane; Schiele, Miriam A; Kollert, Leonie; Weber, Heike; Zwanzger, Peter; Arolt, Volker; Pauli, Paul; Deckert, Jürgen; Reif, Andreas; Domschke, Katharina

2017-04-01

The corticotropin releasing hormone receptor 1 (CRHR1) is crucially involved in the hypothalamic-pituitary-adrenal axis and thus a major regulator of the stress response. CRHR1 gene variation is associated with several mental disorders including anxiety disorders. Studies in rodents have demonstrated epigenetic regulation of CRHR1 gene expression to moderate response to stressful environment. In the present study, we investigated CRHR1 promoter methylation for the first time regarding its role in panic disorder applying a case-control approach (N=131 patients, N=131 controls). In an independent sample of healthy volunteers (N=255), CRHR1 methylation was additionally analyzed for association with the Beck Anxiety Inventory (BAI) score as a dimensional panic-related intermediate phenotype. The functional relevance of altered CRHR1 promoter methylation was investigated by means of luciferase-based reporter gene assays. In panic disorder patients, a significantly decreased CRHR1 methylation was discerned (p<0.001). Accordingly, healthy controls with high BAI scores showed significantly decreased CRHR1 methylation. Functional analyses revealed an increased gene expression in presence of unmethylated as compared to methylated pCpGl_CRHR1 reporter gene vectors. The present study identified a potential role of CRHR1 hypomethylation - conferring increased CRHR1 expression - in panic disorder and a related dimensional intermediate phenotype. This up-regulation of CRHR1 gene expression driven by de-methylation might constitute a link between the stress response and panic disorder risk. Copyright © 2017 Elsevier B.V. and ECNP. All rights reserved.

Effects of non-ablative fractional erbium glass laser treatment on gene regulation in human three-dimensional skin models.

PubMed

Amann, Philipp M; Marquardt, Yvonne; Steiner, Timm; Hölzle, Frank; Skazik-Voogt, Claudia; Heise, Ruth; Baron, Jens M

2016-04-01

Clinical experiences with non-ablative fractional erbium glass laser therapy have demonstrated promising results for dermal remodelling and for the indications of striae, surgical scars and acne scars. So far, molecular effects on human skin following treatment with these laser systems have not been elucidated. Our aim was to investigate laser-induced effects on skin morphology and to analyse molecular effects on gene regulation. Therefore, human three-dimensional (3D) organotypic skin models were irradiated with non-ablative fractional erbium glass laser systems enabling qRT-PCR, microarray and histological studies at same and different time points. A decreased mRNA expression of matrix metalloproteinases (MMPs) 3 and 9 was observed 3 days after treatment. MMP3 also remained downregulated on protein level, whereas the expression of other MMPs like MMP9 was recovered or even upregulated 5 days after irradiation. Inflammatory gene regulatory responses measured by the expression of chemokine (C-X-C motif) ligands (CXCL1, 2, 5, 6) and interleukin expression (IL8) were predominantly reduced. Epidermal differentiation markers such as loricrin, filaggrin-1 and filaggrin-2 were upregulated by both tested laser optics, indicating a potential epidermal involvement. These effects were also shown on protein level in the immunofluorescence analysis. This novel standardised laser-treated human 3D skin model proves useful for monitoring time-dependent ex vivo effects of various laser systems on gene expression and human skin morphology. Our study reveals erbium glass laser-induced regulations of MMP and interleukin expression. We speculate that these alterations on gene expression level could play a role for dermal remodelling, anti-inflammatory effects and increased epidermal differentiation. Our finding may have implications for further understanding of the molecular mechanism of erbium glass laser-induced effects on human skin.

Network regularised Cox regression and multiplex network models to predict disease comorbidities and survival of cancer.

PubMed

Xu, Haoming; Moni, Mohammad Ali; Liò, Pietro

2015-12-01

In cancer genomics, gene expression levels provide important molecular signatures for all types of cancer, and this could be very useful for predicting the survival of cancer patients. However, the main challenge of gene expression data analysis is high dimensionality, and microarray is characterised by few number of samples with large number of genes. To overcome this problem, a variety of penalised Cox proportional hazard models have been proposed. We introduce a novel network regularised Cox proportional hazard model and a novel multiplex network model to measure the disease comorbidities and to predict survival of the cancer patient. Our methods are applied to analyse seven microarray cancer gene expression datasets: breast cancer, ovarian cancer, lung cancer, liver cancer, renal cancer and osteosarcoma. Firstly, we applied a principal component analysis to reduce the dimensionality of original gene expression data. Secondly, we applied a network regularised Cox regression model on the reduced gene expression datasets. By using normalised mutual information method and multiplex network model, we predict the comorbidities for the liver cancer based on the integration of diverse set of omics and clinical data, and we find the diseasome associations (disease-gene association) among different cancers based on the identified common significant genes. Finally, we evaluated the precision of the approach with respect to the accuracy of survival prediction using ROC curves. We report that colon cancer, liver cancer and renal cancer share the CXCL5 gene, and breast cancer, ovarian cancer and renal cancer share the CCND2 gene. Our methods are useful to predict survival of the patient and disease comorbidities more accurately and helpful for improvement of the care of patients with comorbidity. Software in Matlab and R is available on our GitHub page: https://github.com/ssnhcom/NetworkRegularisedCox.git. Copyright © 2015. Published by Elsevier Ltd.

Transcription-dependent radial distribution of TCF7L2 regulated genes in chromosome territories.

PubMed

Torabi, Keyvan; Wangsa, Darawalee; Ponsa, Immaculada; Brown, Markus; Bosch, Anna; Vila-Casadesús, Maria; Karpova, Tatiana S; Calvo, Maria; Castells, Antoni; Miró, Rosa; Ried, Thomas; Camps, Jordi

2017-10-01

Human chromosomes occupy distinct territories in the interphase nucleus. Such chromosome territories (CTs) are positioned according to gene density. Gene-rich CTs are generally located in the center of the nucleus, while gene-poor CTs are positioned more towards the nuclear periphery. However, the association between gene expression levels and the radial positioning of genes within the CT is still under debate. In the present study, we performed three-dimensional fluorescence in situ hybridization experiments in the colorectal cancer cell lines DLD-1 and LoVo using whole chromosome painting probes for chromosomes 8 and 11 and BAC clones targeting four genes with different expression levels assessed by gene expression arrays and RT-PCR. Our results confirmed that the two over-expressed genes, MYC on chromosome 8 and CCND1 on chromosome 11, are located significantly further away from the center of the CT compared to under-expressed genes on the same chromosomes, i.e., DLC1 and SCN3B. When CCND1 expression was reduced after silencing the major transcription factor of the WNT/β-catenin signaling pathway, TCF7L2, the gene was repositioned and mostly detected in the interior of the CT. Thus, we suggest a non-random distribution in which over-expressed genes are located more towards the periphery of the respective CTs.

Predicting Viral Infection From High-Dimensional Biomarker Trajectories

PubMed Central

Chen, Minhua; Zaas, Aimee; Woods, Christopher; Ginsburg, Geoffrey S.; Lucas, Joseph; Dunson, David; Carin, Lawrence

2013-01-01

There is often interest in predicting an individual’s latent health status based on high-dimensional biomarkers that vary over time. Motivated by time-course gene expression array data that we have collected in two influenza challenge studies performed with healthy human volunteers, we develop a novel time-aligned Bayesian dynamic factor analysis methodology. The time course trajectories in the gene expressions are related to a relatively low-dimensional vector of latent factors, which vary dynamically starting at the latent initiation time of infection. Using a nonparametric cure rate model for the latent initiation times, we allow selection of the genes in the viral response pathway, variability among individuals in infection times, and a subset of individuals who are not infected. As we demonstrate using held-out data, this statistical framework allows accurate predictions of infected individuals in advance of the development of clinical symptoms, without labeled data and even when the number of biomarkers vastly exceeds the number of individuals under study. Biological interpretation of several of the inferred pathways (factors) is provided. PMID:23704802

A big data pipeline: Identifying dynamic gene regulatory networks from time-course Gene Expression Omnibus data with applications to influenza infection.

PubMed

Carey, Michelle; Ramírez, Juan Camilo; Wu, Shuang; Wu, Hulin

2018-07-01

A biological host response to an external stimulus or intervention such as a disease or infection is a dynamic process, which is regulated by an intricate network of many genes and their products. Understanding the dynamics of this gene regulatory network allows us to infer the mechanisms involved in a host response to an external stimulus, and hence aids the discovery of biomarkers of phenotype and biological function. In this article, we propose a modeling/analysis pipeline for dynamic gene expression data, called Pipeline4DGEData, which consists of a series of statistical modeling techniques to construct dynamic gene regulatory networks from the large volumes of high-dimensional time-course gene expression data that are freely available in the Gene Expression Omnibus repository. This pipeline has a consistent and scalable structure that allows it to simultaneously analyze a large number of time-course gene expression data sets, and then integrate the results across different studies. We apply the proposed pipeline to influenza infection data from nine studies and demonstrate that interesting biological findings can be discovered with its implementation.

A short treatise concerning a musical approach for the interpretation of gene expression data

PubMed Central

Staege, Martin S.

2015-01-01

Recent technical developments allow the genome-wide and near-complete analysis of gene expression in a given sample, e.g. by usage of high-density DNA microarrays or next generation sequencing. The generated data structure is usually multi-dimensional and requires extensive processing not only for analysis but also for presentation of the results. Today, such data are usually presented graphically, e.g. in the form of heat maps. In the present paper, we propose an alternative form of analysis and presentation which is based on the transformation of gene expression data into sounds that are characterized by their frequency (pitch) and tone duration. Using DNA microarray data from a panel of neuroblastoma and Ewing sarcoma cell lines as well as from Hodgkin’s lymphoma cell lines and normal B cells, we demonstrate that this Gene Expression Music Algorithm (GEMusicA) can be used for discrimination between samples with different biology and for the characterization of differentially expressed genes. PMID:26472273

Gene Expression Dynamics Inspector (GEDI): for integrative analysis of expression profiles

NASA Technical Reports Server (NTRS)

Eichler, Gabriel S.; Huang, Sui; Ingber, Donald E.

2003-01-01

Genome-wide expression profiles contain global patterns that evade visual detection in current gene clustering analysis. Here, a Gene Expression Dynamics Inspector (GEDI) is described that uses self-organizing maps to translate high-dimensional expression profiles of time courses or sample classes into animated, coherent and robust mosaics images. GEDI facilitates identification of interesting patterns of molecular activity simultaneously across gene, time and sample space without prior assumption of any structure in the data, and then permits the user to retrieve genes of interest. Important changes in genome-wide activities may be quickly identified based on 'Gestalt' recognition and hence, GEDI may be especially useful for non-specialist end users, such as physicians. AVAILABILITY: GEDI v1.0 is written in Matlab, and binary Matlab.dll files which require Matlab to run can be downloaded for free by academic institutions at http://www.chip.org/ge/gedihome.html Supplementary information: http://www.chip.org/ge/gedihome.html.

Combining classifiers to predict gene function in Arabidopsis thaliana using large-scale gene expression measurements.

PubMed

Lan, Hui; Carson, Rachel; Provart, Nicholas J; Bonner, Anthony J

2007-09-21

Arabidopsis thaliana is the model species of current plant genomic research with a genome size of 125 Mb and approximately 28,000 genes. The function of half of these genes is currently unknown. The purpose of this study is to infer gene function in Arabidopsis using machine-learning algorithms applied to large-scale gene expression data sets, with the goal of identifying genes that are potentially involved in plant response to abiotic stress. Using in house and publicly available data, we assembled a large set of gene expression measurements for A. thaliana. Using those genes of known function, we first evaluated and compared the ability of basic machine-learning algorithms to predict which genes respond to stress. Predictive accuracy was measured using ROC50 and precision curves derived through cross validation. To improve accuracy, we developed a method for combining these classifiers using a weighted-voting scheme. The combined classifier was then trained on genes of known function and applied to genes of unknown function, identifying genes that potentially respond to stress. Visual evidence corroborating the predictions was obtained using electronic Northern analysis. Three of the predicted genes were chosen for biological validation. Gene knockout experiments confirmed that all three are involved in a variety of stress responses. The biological analysis of one of these genes (At1g16850) is presented here, where it is shown to be necessary for the normal response to temperature and NaCl. Supervised learning methods applied to large-scale gene expression measurements can be used to predict gene function. However, the ability of basic learning methods to predict stress response varies widely and depends heavily on how much dimensionality reduction is used. Our method of combining classifiers can improve the accuracy of such predictions - in this case, predictions of genes involved in stress response in plants - and it effectively chooses the appropriate amount of dimensionality reduction automatically. The method provides a useful means of identifying genes in A. thaliana that potentially respond to stress, and we expect it would be useful in other organisms and for other gene functions.

Generation of siRNA Nanosheets for Efficient RNA Interference

NASA Astrophysics Data System (ADS)

Kim, Hyejin; Lee, Jae Sung; Lee, Jong Bum

2016-04-01

After the discovery of small interference RNA (siRNA), nanostructured siRNA delivery systems have been introduced to achieve an efficient regulation of the target gene expression. Here we report a new siRNA-generating two dimensional nanostructure in a formation of nanosized sheet. Inspired by tunable mechanical and functional properties of the previously reported RNA membrane, siRNA nanosized sheets (siRNA-NS) with multiple Dicer cleavage sites were prepared. The siRNA-NS has two dimensional structure, providing a large surface area for Dicer to cleave the siRNA-NS for the generation of functional siRNAs. Furthermore, downregulation of the cellular target gene expression was achieved by delivery of siRNA-NS without chemical modification of RNA strands or conjugation to other substances.

Spatial fluctuations in expression of the heterocyst differentiation regulatory gene hetR in Anabaena filaments.

PubMed

Corrales-Guerrero, Laura; Tal, Asaf; Arbel-Goren, Rinat; Mariscal, Vicente; Flores, Enrique; Herrero, Antonia; Stavans, Joel

2015-04-01

Under nitrogen deprivation, filaments of the cyanobacterium Anabaena undergo a process of development, resulting in a one-dimensional pattern of nitrogen-fixing heterocysts separated by about ten photosynthetic vegetative cells. Many aspects of gene expression before nitrogen deprivation and during the developmental process remain to be elucidated. Furthermore, the coupling of gene expression fluctuations between cells along a multicellular filament is unknown. We studied the statistics of fluctuations of gene expression of HetR, a transcription factor essential for heterocyst differentiation, both under steady-state growth in nitrogen-rich conditions and at different times following nitrogen deprivation, using a chromosomally-encoded translational hetR-gfp fusion. Statistical analysis of fluorescence at the individual cell level in wild-type and mutant filaments demonstrates that expression fluctuations of hetR in nearby cells are coupled, with a characteristic spatial range of circa two to three cells, setting the scale for cellular interactions along a filament. Correlations between cells predominantly arise from intercellular molecular transfer and less from cell division. Fluctuations after nitrogen step-down can build up on those under nitrogen-replete conditions. We found that under nitrogen-rich conditions, basal, steady-state expression of the HetR inhibitor PatS, cell-cell communication influenced by the septal protein SepJ and positive HetR auto-regulation are essential determinants of fluctuations in hetR expression and its distribution along filaments. A comparison between the expression of hetR-gfp under nitrogen-rich and nitrogen-poor conditions highlights the differences between the two HetR inhibitors PatS and HetN, as well as the differences in specificity between the septal proteins SepJ and FraC/FraD. Activation, inhibition and cell-cell communication lie at the heart of developmental processes. Our results show that proteins involved in these basic ingredients combine together in the presence of inevitable stochasticity in gene expression, to control the coupled fluctuations of gene expression that give rise to a one-dimensional developmental pattern in this organism.

Integrated analysis of DNA-methylation and gene expression using high-dimensional penalized regression: a cohort study on bone mineral density in postmenopausal women.

PubMed

Lien, Tonje G; Borgan, Ørnulf; Reppe, Sjur; Gautvik, Kaare; Glad, Ingrid Kristine

2018-03-07

Using high-dimensional penalized regression we studied genome-wide DNA-methylation in bone biopsies of 80 postmenopausal women in relation to their bone mineral density (BMD). The women showed BMD varying from severely osteoporotic to normal. Global gene expression data from the same individuals was available, and since DNA-methylation often affects gene expression, the overall aim of this paper was to include both of these omics data sets into an integrated analysis. The classical penalized regression uses one penalty, but we incorporated individual penalties for each of the DNA-methylation sites. These individual penalties were guided by the strength of association between DNA-methylations and gene transcript levels. DNA-methylations that were highly associated to one or more transcripts got lower penalties and were therefore favored compared to DNA-methylations showing less association to expression. Because of the complex pathways and interactions among genes, we investigated both the association between DNA-methylations and their corresponding cis gene, as well as the association between DNA-methylations and trans-located genes. Two integrating penalized methods were used: first, an adaptive group-regularized ridge regression, and secondly, variable selection was performed through a modified version of the weighted lasso. When information from gene expressions was integrated, predictive performance was considerably improved, in terms of predictive mean square error, compared to classical penalized regression without data integration. We found a 14.7% improvement in the ridge regression case and a 17% improvement for the lasso case. Our version of the weighted lasso with data integration found a list of 22 interesting methylation sites. Several corresponded to genes that are known to be important in bone formation. Using BMD as response and these 22 methylation sites as covariates, least square regression analyses resulted in R 2 =0.726, comparable to an average R 2 =0.438 for 10000 randomly selected groups of DNA-methylations with group size 22. Two recent types of penalized regression methods were adapted to integrate DNA-methylation and their association to gene expression in the analysis of bone mineral density. In both cases predictions clearly benefit from including the additional information on gene expressions.

Regularization Methods for High-Dimensional Instrumental Variables Regression With an Application to Genetical Genomics

PubMed Central

Lin, Wei; Feng, Rui; Li, Hongzhe

2014-01-01

In genetical genomics studies, it is important to jointly analyze gene expression data and genetic variants in exploring their associations with complex traits, where the dimensionality of gene expressions and genetic variants can both be much larger than the sample size. Motivated by such modern applications, we consider the problem of variable selection and estimation in high-dimensional sparse instrumental variables models. To overcome the difficulty of high dimensionality and unknown optimal instruments, we propose a two-stage regularization framework for identifying and estimating important covariate effects while selecting and estimating optimal instruments. The methodology extends the classical two-stage least squares estimator to high dimensions by exploiting sparsity using sparsity-inducing penalty functions in both stages. The resulting procedure is efficiently implemented by coordinate descent optimization. For the representative L1 regularization and a class of concave regularization methods, we establish estimation, prediction, and model selection properties of the two-stage regularized estimators in the high-dimensional setting where the dimensionality of co-variates and instruments are both allowed to grow exponentially with the sample size. The practical performance of the proposed method is evaluated by simulation studies and its usefulness is illustrated by an analysis of mouse obesity data. Supplementary materials for this article are available online. PMID:26392642

Mifepristone inhibits extracellular matrix formation in uterine leiomyoma.

PubMed

Patel, Amrita; Malik, Minnie; Britten, Joy; Cox, Jeris; Catherino, William H

2016-04-01

To characterize the efficacy of mifepristone treatment on extracellular matrix (ECM) production in leiomyomas. Laboratory study. University research laboratory. None. Treatment of human immortalized two-dimensional (2D) and three-dimensional (3D) leiomyoma and myometrial cells with mifepristone and the progestin promegestone (R5020). Expression of COL1A1, fibronectin, versican variant V0, and dermatopontin in treated leiomyoma cells by Western blot analysis and confirmatory immunohistochemistry staining of treated 3D cultures. Treatment with progestin stimulated production of COL1A1, fibronectin, versican, and dermatopontin. Mifepristone treatment inhibited protein production of these genes, most notably with versican expression. Combination treatment with both the agonist and antagonist further inhibited protein expression of these genes. Immunohistochemistry performed on 3D cultures demonstrated generalized inhibition of ECM protein concentration. Our study demonstrated that the progesterone agonist R5020 directly stimulated extracellular matrix components COL1A1, fibronectin, versican, and dermatopontin production in human leiomyoma cells. Progesterone antagonist mifepristone decreased protein production of these genes to levels comparable with untreated leiomyoma cells. Published by Elsevier Inc.

SEURAT: Visual analytics for the integrated analysis of microarray data

PubMed Central

2010-01-01

Background In translational cancer research, gene expression data is collected together with clinical data and genomic data arising from other chip based high throughput technologies. Software tools for the joint analysis of such high dimensional data sets together with clinical data are required. Results We have developed an open source software tool which provides interactive visualization capability for the integrated analysis of high-dimensional gene expression data together with associated clinical data, array CGH data and SNP array data. The different data types are organized by a comprehensive data manager. Interactive tools are provided for all graphics: heatmaps, dendrograms, barcharts, histograms, eventcharts and a chromosome browser, which displays genetic variations along the genome. All graphics are dynamic and fully linked so that any object selected in a graphic will be highlighted in all other graphics. For exploratory data analysis the software provides unsupervised data analytics like clustering, seriation algorithms and biclustering algorithms. Conclusions The SEURAT software meets the growing needs of researchers to perform joint analysis of gene expression, genomical and clinical data. PMID:20525257

Joint mapping of genes and conditions via multidimensional unfolding analysis

PubMed Central

Van Deun, Katrijn; Marchal, Kathleen; Heiser, Willem J; Engelen, Kristof; Van Mechelen, Iven

2007-01-01

Background Microarray compendia profile the expression of genes in a number of experimental conditions. Such data compendia are useful not only to group genes and conditions based on their similarity in overall expression over profiles but also to gain information on more subtle relations between genes and conditions. Getting a clear visual overview of all these patterns in a single easy-to-grasp representation is a useful preliminary analysis step: We propose to use for this purpose an advanced exploratory method, called multidimensional unfolding. Results We present a novel algorithm for multidimensional unfolding that overcomes both general problems and problems that are specific for the analysis of gene expression data sets. Applying the algorithm to two publicly available microarray compendia illustrates its power as a tool for exploratory data analysis: The unfolding analysis of a first data set resulted in a two-dimensional representation which clearly reveals temporal regulation patterns for the genes and a meaningful structure for the time points, while the analysis of a second data set showed the algorithm's ability to go beyond a mere identification of those genes that discriminate between different patient or tissue types. Conclusion Multidimensional unfolding offers a useful tool for preliminary explorations of microarray data: By relying on an easy-to-grasp low-dimensional geometric framework, relations among genes, among conditions and between genes and conditions are simultaneously represented in an accessible way which may reveal interesting patterns in the data. An additional advantage of the method is that it can be applied to the raw data without necessitating the choice of suitable genewise transformations of the data. PMID:17550582

An efficient method to identify differentially expressed genes in microarray experiments

PubMed Central

Qin, Huaizhen; Feng, Tao; Harding, Scott A.; Tsai, Chung-Jui; Zhang, Shuanglin

2013-01-01

Motivation Microarray experiments typically analyze thousands to tens of thousands of genes from small numbers of biological replicates. The fact that genes are normally expressed in functionally relevant patterns suggests that gene-expression data can be stratified and clustered into relatively homogenous groups. Cluster-wise dimensionality reduction should make it feasible to improve screening power while minimizing information loss. Results We propose a powerful and computationally simple method for finding differentially expressed genes in small microarray experiments. The method incorporates a novel stratification-based tight clustering algorithm, principal component analysis and information pooling. Comprehensive simulations show that our method is substantially more powerful than the popular SAM and eBayes approaches. We applied the method to three real microarray datasets: one from a Populus nitrogen stress experiment with 3 biological replicates; and two from public microarray datasets of human cancers with 10 to 40 biological replicates. In all three analyses, our method proved more robust than the popular alternatives for identification of differentially expressed genes. Availability The C++ code to implement the proposed method is available upon request for academic use. PMID:18453554

Integrative analysis of gene expression and DNA methylation using unsupervised feature extraction for detecting candidate cancer biomarkers.

PubMed

Moon, Myungjin; Nakai, Kenta

2018-04-01

Currently, cancer biomarker discovery is one of the important research topics worldwide. In particular, detecting significant genes related to cancer is an important task for early diagnosis and treatment of cancer. Conventional studies mostly focus on genes that are differentially expressed in different states of cancer; however, noise in gene expression datasets and insufficient information in limited datasets impede precise analysis of novel candidate biomarkers. In this study, we propose an integrative analysis of gene expression and DNA methylation using normalization and unsupervised feature extractions to identify candidate biomarkers of cancer using renal cell carcinoma RNA-seq datasets. Gene expression and DNA methylation datasets are normalized by Box-Cox transformation and integrated into a one-dimensional dataset that retains the major characteristics of the original datasets by unsupervised feature extraction methods, and differentially expressed genes are selected from the integrated dataset. Use of the integrated dataset demonstrated improved performance as compared with conventional approaches that utilize gene expression or DNA methylation datasets alone. Validation based on the literature showed that a considerable number of top-ranked genes from the integrated dataset have known relationships with cancer, implying that novel candidate biomarkers can also be acquired from the proposed analysis method. Furthermore, we expect that the proposed method can be expanded for applications involving various types of multi-omics datasets.

In vitro evaluation of three-dimensional single-walled carbon nanotube composites for bone tissue engineering.

PubMed

Gupta, Ashim; Main, Benjamin J; Taylor, Brittany L; Gupta, Manu; Whitworth, Craig A; Cady, Craig; Freeman, Joseph W; El-Amin, Saadiq F

2014-11-01

The purpose of this study was to develop three-dimensional single-walled carbon nanotube composites (SWCNT/PLAGA) using 10-mg single-walled carbon nanotubes (SWCNT) for bone regeneration and to determine the mechanical strength of the composites, and to evaluate the interaction of MC3T3-E1 cells via cell adhesion, growth, survival, proliferation, and gene expression. PLAGA (polylactic-co-glycolic acid) and SWCNT/PLAGA microspheres and composites were fabricated, characterized, and mechanical testing was performed. MC3T3-E1 cells were seeded and cell adhesion/morphology, growth/survival, proliferation, and gene expression analysis were performed to evaluate biocompatibility. Imaging studies demonstrated microspheres with uniform shape and smooth surfaces, and uniform incorporation of SWCNT into PLAGA matrix. The microspheres bonded in a random packing manner while maintaining spacing, thus resembling trabeculae of cancellous bone. Addition of SWCNT led to greater compressive modulus and ultimate compressive strength. Imaging studies revealed that MC3T3-E1 cells adhered, grew/survived, and exhibited normal, nonstressed morphology on the composites. SWCNT/PLAGA composites exhibited higher cell proliferation rate and gene expression compared with PLAGA. These results demonstrate the potential of SWCNT/PLAGA composites for musculoskeletal regeneration, for bone tissue engineering, and are promising for orthopedic applications as they possess the combined effect of increased mechanical strength, cell proliferation, and gene expression. © 2014 Wiley Periodicals, Inc.

Study of Tnp1, Tekt1, and Plzf Genes Expression During an in vitro Three-Dimensional Neonatal Male Mice Testis Culture

PubMed

Alrahel, Ahmad; Movahedin, Mansoureh; Mazaheri, Zohre; Amidi, Fardin

2018-07-01

In vitro spermatogenesis has a long research history beginning in the early 20th century. This organ culture method was therefore abandoned, and alternative cell culture methods were chosen by many researchers. Here, whether Tnp1, Tekt1, and Plzf, which play a crucial role in spermatogenesis, can be expressed during testis organ culture was assessed. Testes of 10 mouse pups were first removed, and the testis tissue was then separated into smaller pieces of seminiferous tubules. The size of the pieces was arbitrary; approximately 1 mg in weight or 1 mm3 in size when compacted. Afterwards, the testis tissue fragments (1–3) were transferred to the hexahedrons, incubated in a culture incubator and cultured for 12 weeks. Histological assessment and molecular evaluation were carried out at the end of the study. The results showed that the expression of Tekt1 as a mitotic gene in mouse pups decreased significantly (p ≤ 0.05) in comparison to adult mouse testis. Meanwhile, the expression of Tnp1 as a meiotic gene increased significantly (p ≤ 0.05) as compared to neonate mouse testis at the beginning of the culture. The expression of Plzf showed no significant difference during the 12 weeks of culture (p ≥ 0.05). Based on histological study, different types of spermatocytes and post-meiotic stages of germ cells could not be detected. This kind of three-dimensional culture can induce expression of post-meiotic gene, Tnp1, but only at the molecular level and not beyond meiosis.

Upregulated epidermal growth factor receptor expression following near-infrared irradiation simulating solar radiation in a three-dimensional reconstructed human corneal epithelial tissue culture model.

PubMed

Tanaka, Yohei; Nakayama, Jun

2016-01-01

Humans are increasingly exposed to near-infrared (NIR) radiation from both natural (eg, solar) and artificial (eg, electrical appliances) sources. Although the biological effects of sun and ultraviolet (UV) exposure have been extensively investigated, the biological effect of NIR radiation is still unclear. We previously reported that NIR as well as UV induces photoaging and standard UV-blocking materials, such as sunglasses, do not sufficiently block NIR. The objective of this study was to investigate changes in gene expression in three-dimensional reconstructed corneal epithelial tissue culture exposed to broad-spectrum NIR irradiation to simulate solar NIR radiation that reaches human tissues. DNA microarray and quantitative real-time polymerase chain reaction analysis were used to assess gene expression levels in a three-dimensional reconstructed corneal epithelial model composed of normal human corneal epithelial cells exposed to water-filtered broad-spectrum NIR irradiation with a contact cooling (20°C). The water-filter allowed 1,000-1,800 nm wavelengths and excluded 1,400-1,500 nm wavelengths. A DNA microarray with >62,000 different probes showed 25 and 150 genes that were up- or downregulated by at least fourfold and twofold, respectively, after NIR irradiation. In particular, epidermal growth factor receptor (EGFR) was upregulated by 19.4-fold relative to control cells. Quantitative real-time polymerase chain reaction analysis revealed that two variants of EGFR in human corneal epithelial tissue were also significantly upregulated after five rounds of 10 J/cm(2) irradiation (P<0.05). We found that NIR irradiation induced the upregulated expression of EGFR in human corneal cells. Since over half of the solar energy reaching the Earth is in the NIR region, which cannot be adequately blocked by eyewear and thus can induce eye damage with intensive or long-term exposure, protection from both UV and NIR radiation may prevent changes in gene expression and in turn eye damage.

Genes@Work: an efficient algorithm for pattern discovery and multivariate feature selection in gene expression data.

PubMed

Lepre, Jorge; Rice, J Jeremy; Tu, Yuhai; Stolovitzky, Gustavo

2004-05-01

Despite the growing literature devoted to finding differentially expressed genes in assays probing different tissues types, little attention has been paid to the combinatorial nature of feature selection inherent to large, high-dimensional gene expression datasets. New flexible data analysis approaches capable of searching relevant subgroups of genes and experiments are needed to understand multivariate associations of gene expression patterns with observed phenotypes. We present in detail a deterministic algorithm to discover patterns of multivariate gene associations in gene expression data. The patterns discovered are differential with respect to a control dataset. The algorithm is exhaustive and efficient, reporting all existent patterns that fit a given input parameter set while avoiding enumeration of the entire pattern space. The value of the pattern discovery approach is demonstrated by finding a set of genes that differentiate between two types of lymphoma. Moreover, these genes are found to behave consistently in an independent dataset produced in a different laboratory using different arrays, thus validating the genes selected using our algorithm. We show that the genes deemed significant in terms of their multivariate statistics will be missed using other methods. Our set of pattern discovery algorithms including a user interface is distributed as a package called Genes@Work. This package is freely available to non-commercial users and can be downloaded from our website (http://www.research.ibm.com/FunGen).

A preliminary result of three-dimensional microarray technology to gene analysis with endoscopic ultrasound-guided fine-needle aspiration specimens and pancreatic juices

PubMed Central

2010-01-01

Background Analysis of gene expression and gene mutation may add information to be different from ordinary pathological tissue diagnosis. Since samples obtained endoscopically are very small, it is desired that more sensitive technology is developed for gene analysis. We investigated whether gene expression and gene mutation analysis by newly developed ultra-sensitive three-dimensional (3D) microarray is possible using small amount samples from endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) specimens and pancreatic juices. Methods Small amount samples from 17 EUS-FNA specimens and 16 pancreatic juices were obtained. After nucleic acid extraction, the samples were amplified with labeling and analyzed by the 3D microarray. Results The analyzable rate with the microarray was 46% (6/13) in EUS-FNA specimens of RNAlater® storage, and RNA degradations were observed in all the samples of frozen storage. In pancreatic juices, the analyzable rate was 67% (4/6) in frozen storage samples and 20% (2/10) in RNAlater® storage. EUS-FNA specimens were classified into cancer and non-cancer by gene expression analysis and K-ras codon 12 mutations were also detected using the 3D microarray. Conclusions Gene analysis from small amount samples obtained endoscopically was possible by newly developed 3D microarray technology. High quality RNA from EUS-FNA samples were obtained and remained in good condition only using RNA stabilizer. In contrast, high quality RNA from pancreatic juice samples were obtained only in frozen storage without RNA stabilizer. PMID:20416107

Transcriptome Dynamics of Developing Photoreceptors in Three‐Dimensional Retina Cultures Recapitulates Temporal Sequence of Human Cone and Rod Differentiation Revealing Cell Surface Markers and Gene Networks

PubMed Central

Kaewkhaw, Rossukon; Kaya, Koray Dogan; Brooks, Matthew; Homma, Kohei; Zou, Jizhong; Chaitankar, Vijender; Rao, Mahendra

2015-01-01

Abstract The derivation of three‐dimensional (3D) stratified neural retina from pluripotent stem cells has permitted investigations of human photoreceptors. We have generated a H9 human embryonic stem cell subclone that carries a green fluorescent protein (GFP) reporter under the control of the promoter of cone‐rod homeobox (CRX), an established marker of postmitotic photoreceptor precursors. The CRXp‐GFP reporter replicates endogenous CRX expression in vitro when the H9 subclone is induced to form self‐organizing 3D retina‐like tissue. At day 37, CRX+ photoreceptors appear in the basal or middle part of neural retina and migrate to apical side by day 67. Temporal and spatial patterns of retinal cell type markers recapitulate the predicted sequence of development. Cone gene expression is concomitant with CRX, whereas rod differentiation factor neural retina leucine zipper protein (NRL) is first observed at day 67. At day 90, robust expression of NRL and its target nuclear receptor NR2E3 is evident in many CRX+ cells, while minimal S‐opsin and no rhodopsin or L/M‐opsin is present. The transcriptome profile, by RNA‐seq, of developing human photoreceptors is remarkably concordant with mRNA and immunohistochemistry data available for human fetal retina although many targets of CRX, including phototransduction genes, exhibit a significant delay in expression. We report on temporal changes in gene signatures, including expression of cell surface markers and transcription factors; these expression changes should assist in isolation of photoreceptors at distinct stages of differentiation and in delineating coexpression networks. Our studies establish the first global expression database of developing human photoreceptors, providing a reference map for functional studies in retinal cultures. Stem Cells 2015;33:3504–3518 PMID:26235913

Replication pattern of the pericentromeric region of chromosome 10q and expression of the RET protooncogene.

PubMed

Cinti, R; Schena, F; Passalacqua, M; Ceccherini, I; Ravazzolo, R

2004-08-15

Regulation of the RET gene is highly specific during embryo development and is strictly tissue-specific. Control of transcription depends on mechanisms influenced by epigenetic processes, in particular, histone acetylation at regions flanking the 5' end of the gene. Since the RET gene is mapped in the pericentromeric region of the human chromosome 10, the implication of epigenetic processes is even more striking and worth to be investigated in an extended chromosomal tract. One experimental approach to study the chromatin status in relationship with gene transcription is to assess the replication timing, which we did by using fluorescent in situ hybridization in cells expressing or not expressing the RET gene. By using probes spanning a 700-kb genomic region from the RET locus toward the centromere, we found a relationship between RET expression and early replication. Different patterns were observed between cells naturally expressing RET and cells induced to expression of RET by treatment with sodium butyrate, an inhibitor of histone deacetylases. Three-dimensional analysis of the nuclear localization of fluorescent signals by confocal microscopy showed difference of localization between the RET probe and a probe for a housekeeping gene, G3PDH, located at 12p13.3, in cells that do not express RET, in accordance with previous data for other genes and chromosomal regions. However, RET-expressing cells showed a localization of signals which was not consistent with that expected for expressed genes.

Gene selection for microarray data classification via subspace learning and manifold regularization.

PubMed

Tang, Chang; Cao, Lijuan; Zheng, Xiao; Wang, Minhui

2017-12-19

With the rapid development of DNA microarray technology, large amount of genomic data has been generated. Classification of these microarray data is a challenge task since gene expression data are often with thousands of genes but a small number of samples. In this paper, an effective gene selection method is proposed to select the best subset of genes for microarray data with the irrelevant and redundant genes removed. Compared with original data, the selected gene subset can benefit the classification task. We formulate the gene selection task as a manifold regularized subspace learning problem. In detail, a projection matrix is used to project the original high dimensional microarray data into a lower dimensional subspace, with the constraint that the original genes can be well represented by the selected genes. Meanwhile, the local manifold structure of original data is preserved by a Laplacian graph regularization term on the low-dimensional data space. The projection matrix can serve as an importance indicator of different genes. An iterative update algorithm is developed for solving the problem. Experimental results on six publicly available microarray datasets and one clinical dataset demonstrate that the proposed method performs better when compared with other state-of-the-art methods in terms of microarray data classification. Graphical Abstract The graphical abstract of this work.

Production of functional proteins: balance of shear stress and gravity

NASA Technical Reports Server (NTRS)

Kaysen, James Howard (Inventor); Hammond, Timothy Grant (Inventor); Goodwin, Thomas John (Inventor)

2011-01-01

A method for the production of functional proteins including hormones by renal cells in a three dimensional culturing process responsive to shear stress uses a rotating wall vessel. Natural mixture of renal cells expresses the enzyme 1-.alpha.-hydroxylase which can be used to generate the active form of vitamin D: 1,25-diOH vitamin D.sub.3. The fibroblast cultures and co-culture of renal cortical cells express the gene for erythropoietin and secrete erythropoietin into the culture supernatant. Other shear stress response genes are also modulated by shear stress, such as toxin receptors megalin and cubulin (gp280). Also provided is a method of treating an in-need individual with the functional proteins produced in a three dimensional co-culture process responsive to shear stress using a rotating wall vessel.

An overview of techniques for linking high-dimensional molecular data to time-to-event endpoints by risk prediction models.

PubMed

Binder, Harald; Porzelius, Christine; Schumacher, Martin

2011-03-01

Analysis of molecular data promises identification of biomarkers for improving prognostic models, thus potentially enabling better patient management. For identifying such biomarkers, risk prediction models can be employed that link high-dimensional molecular covariate data to a clinical endpoint. In low-dimensional settings, a multitude of statistical techniques already exists for building such models, e.g. allowing for variable selection or for quantifying the added value of a new biomarker. We provide an overview of techniques for regularized estimation that transfer this toward high-dimensional settings, with a focus on models for time-to-event endpoints. Techniques for incorporating specific covariate structure are discussed, as well as techniques for dealing with more complex endpoints. Employing gene expression data from patients with diffuse large B-cell lymphoma, some typical modeling issues from low-dimensional settings are illustrated in a high-dimensional application. First, the performance of classical stepwise regression is compared to stage-wise regression, as implemented by a component-wise likelihood-based boosting approach. A second issues arises, when artificially transforming the response into a binary variable. The effects of the resulting loss of efficiency and potential bias in a high-dimensional setting are illustrated, and a link to competing risks models is provided. Finally, we discuss conditions for adequately quantifying the added value of high-dimensional gene expression measurements, both at the stage of model fitting and when performing evaluation. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Shrinkage estimation of effect sizes as an alternative to hypothesis testing followed by estimation in high-dimensional biology: applications to differential gene expression.

PubMed

Montazeri, Zahra; Yanofsky, Corey M; Bickel, David R

2010-01-01

Research on analyzing microarray data has focused on the problem of identifying differentially expressed genes to the neglect of the problem of how to integrate evidence that a gene is differentially expressed with information on the extent of its differential expression. Consequently, researchers currently prioritize genes for further study either on the basis of volcano plots or, more commonly, according to simple estimates of the fold change after filtering the genes with an arbitrary statistical significance threshold. While the subjective and informal nature of the former practice precludes quantification of its reliability, the latter practice is equivalent to using a hard-threshold estimator of the expression ratio that is not known to perform well in terms of mean-squared error, the sum of estimator variance and squared estimator bias. On the basis of two distinct simulation studies and data from different microarray studies, we systematically compared the performance of several estimators representing both current practice and shrinkage. We find that the threshold-based estimators usually perform worse than the maximum-likelihood estimator (MLE) and they often perform far worse as quantified by estimated mean-squared risk. By contrast, the shrinkage estimators tend to perform as well as or better than the MLE and never much worse than the MLE, as expected from what is known about shrinkage. However, a Bayesian measure of performance based on the prior information that few genes are differentially expressed indicates that hard-threshold estimators perform about as well as the local false discovery rate (FDR), the best of the shrinkage estimators studied. Based on the ability of the latter to leverage information across genes, we conclude that the use of the local-FDR estimator of the fold change instead of informal or threshold-based combinations of statistical tests and non-shrinkage estimators can be expected to substantially improve the reliability of gene prioritization at very little risk of doing so less reliably. Since the proposed replacement of post-selection estimates with shrunken estimates applies as well to other types of high-dimensional data, it could also improve the analysis of SNP data from genome-wide association studies.

Identification of Methanococcus Jannaschii Proteins in 2-D Gel Electrophoresis Patterns by Mass Spectrometry

DOE R&D Accomplishments Database

Liang, X.

1998-06-10

The genome of Methanococcus jannaschii has been sequenced completely and has been found to contain approximately 1,770 predicted protein-coding regions. When these coding regions are expressed and how their expression is regulated, however, remain open questions. In this work, mass spectrometry was combined with two-dimensional gel electrophoresis to identify which proteins the genes produce under different growth conditions, and thus investigate the regulation of genes responsible for functions characteristic of this thermophilic representative of the methanogenic Archaea.

Three-dimensional hepatocyte culture system for the study of Echinococcus multilocularis larval development

PubMed Central

Chen, Bing; Yan, Hongbin; Zhao, Yannan; Lou, Zhongzi; Li, Jianqiu; Fu, Baoquan; Zhu, Xingquan; McManus, Donald P.; Dai, Jianwu; Jia, Wanzhong

2018-01-01

Background Hepatocyte-based metacestode culture is an attractive method to study alveolar echinococcosis (AE), but it is limited by the relatively short lifespan of cultured hepatocytes in maintaining their normal function. Methodology/principal findings We describe a three-dimensional (3D) hepatic culture system developed from co-cultured hepatocytes and mesenchymal stem cells using a collagen scaffold to study the development of Echinococcus multilocularis larvae. This 3D culture system preserved the function of hepatocytes for a longer period of time than their monolayer counterparts, with albumin secretion, 7-ethoxyresorufin O-deethylation activity, urea synthesis, CYP3A4 and CYP2D6 activity being highly preserved for 21–28 days. The expression levels of hepatocyte-specific genes including CLDN-3, Bsep, AFP, G6P, A1AT, CYP3A4 and NR1I3 were significantly higher in the 3D cultured system compared with their monolayer counterparts after 14-days in culture. Additionally, in the presence of 3D cultured hepatocytes, 81.2% of E. multilocularis protoscoleces rapidly de-differentiated into infective vesicles within eight weeks. Transcriptomic analyses revealed 807 differentially expressed genes between cultured vesicles and protoscoleces, including 119 genes uniquely expressed in protoscoleces, and 242 genes uniquely expressed in vesicles. These differentially expressed genes were mainly involved in parasite growth relating to the G-protein coupled receptor activity pathway, substrate-specific transmembrane transporter activity, cell-cell adhesion process, and potentially with neuroactive ligand-receptor interaction. Conclusions/significance This culture system provides a valuable advance in prolonging hepatocyte functionality, a foundation for future in-depth analysis of the host-parasite interaction in AE, and a useful model to evaluate potential therapeutic strategies to treat AE. PMID:29538424

Chitosan-based DNA delivery vector targeted to gonadotropin-releasing hormone (GnRH) receptor.

PubMed

Boonthum, Chatwalee; Namdee, Katawut; Boonrungsiman, Suwimon; Chatdarong, Kaywalee; Saengkrit, Nattika; Sajomsang, Warayuth; Ponglowhapan, Suppawiwat; Yata, Teerapong

2017-02-10

The main purpose of this study was to investigate the application of modified chitosan as a potential vector for gene delivery to gonadotropin-releasing hormone receptor (GnRHR)-expressing cells. Such design of gene carrier could be useful in particular for gene therapy for cancers related to the reproductive system, gene disorders of sexual development, and contraception and fertility control. In this study, a decapeptide GnRH was successfully conjugated to chitosan (CS) as confirmed by proton nuclear magnetic resonance spectroscopy ( 1 H NMR) and Attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR). The synthesized GnRH-conjugated chitosan (GnRH-CS) was able to condense DNA to form positively charged nanoparticles and specifically deliver plasmid DNA to targeted cells in both two-dimensional (2D) and three-dimensional (3D) cell cultures systems. Importantly, GnRH-CS exhibited higher transfection activity compared to unmodified CS. In conclusion, GnRH-conjugated chitosan can be a promising carrier for targeted DNA delivery to GnRHR-expressing cells. Copyright © 2016 Elsevier Ltd. All rights reserved.

Mapping eQTL Networks with Mixed Graphical Markov Models

PubMed Central

Tur, Inma; Roverato, Alberto; Castelo, Robert

2014-01-01

Expression quantitative trait loci (eQTL) mapping constitutes a challenging problem due to, among other reasons, the high-dimensional multivariate nature of gene-expression traits. Next to the expression heterogeneity produced by confounding factors and other sources of unwanted variation, indirect effects spread throughout genes as a result of genetic, molecular, and environmental perturbations. From a multivariate perspective one would like to adjust for the effect of all of these factors to end up with a network of direct associations connecting the path from genotype to phenotype. In this article we approach this challenge with mixed graphical Markov models, higher-order conditional independences, and q-order correlation graphs. These models show that additive genetic effects propagate through the network as function of gene–gene correlations. Our estimation of the eQTL network underlying a well-studied yeast data set leads to a sparse structure with more direct genetic and regulatory associations that enable a straightforward comparison of the genetic control of gene expression across chromosomes. Interestingly, it also reveals that eQTLs explain most of the expression variability of network hub genes. PMID:25271303

Independence screening for high dimensional nonlinear additive ODE models with applications to dynamic gene regulatory networks.

PubMed

Xue, Hongqi; Wu, Shuang; Wu, Yichao; Ramirez Idarraga, Juan C; Wu, Hulin

2018-05-02

Mechanism-driven low-dimensional ordinary differential equation (ODE) models are often used to model viral dynamics at cellular levels and epidemics of infectious diseases. However, low-dimensional mechanism-based ODE models are limited for modeling infectious diseases at molecular levels such as transcriptomic or proteomic levels, which is critical to understand pathogenesis of diseases. Although linear ODE models have been proposed for gene regulatory networks (GRNs), nonlinear regulations are common in GRNs. The reconstruction of large-scale nonlinear networks from time-course gene expression data remains an unresolved issue. Here, we use high-dimensional nonlinear additive ODEs to model GRNs and propose a 4-step procedure to efficiently perform variable selection for nonlinear ODEs. To tackle the challenge of high dimensionality, we couple the 2-stage smoothing-based estimation method for ODEs and a nonlinear independence screening method to perform variable selection for the nonlinear ODE models. We have shown that our method possesses the sure screening property and it can handle problems with non-polynomial dimensionality. Numerical performance of the proposed method is illustrated with simulated data and a real data example for identifying the dynamic GRN of Saccharomyces cerevisiae. Copyright © 2018 John Wiley & Sons, Ltd.

3D confocal reconstruction of gene expression in mouse.

PubMed

Hecksher-Sørensen, J; Sharpe, J

2001-01-01

Three-dimensional computer reconstructions of gene expression data will become a valuable tool in biomedical research in the near future. However, at present the process of converting in situ expression data into 3D models is a highly specialized and time-consuming procedure. Here we present a method which allows rapid reconstruction of whole-mount in situ data from mouse embryos. Mid-gestation embryos were stained with the alkaline phosphotase substrate Fast Red, which can be detected using confocal laser scanning microscopy (CLSM), and cut into 70 microm sections. Each section was then scanned and digitally reconstructed. Using this method it took two days to section, digitize and reconstruct the full expression pattern of Shh in an E9.5 embryo (a 3D model of this embryo can be seen at genex.hgu.mrc.ac.uk). Additionally we demonstrate that this technique allows gene expression to be studied at the single cell level in intact tissue.

Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks

PubMed Central

Marbach, Daniel; Roy, Sushmita; Ay, Ferhat; Meyer, Patrick E.; Candeias, Rogerio; Kahveci, Tamer; Bristow, Christopher A.; Kellis, Manolis

2012-01-01

Gaining insights on gene regulation from large-scale functional data sets is a grand challenge in systems biology. In this article, we develop and apply methods for transcriptional regulatory network inference from diverse functional genomics data sets and demonstrate their value for gene function and gene expression prediction. We formulate the network inference problem in a machine-learning framework and use both supervised and unsupervised methods to predict regulatory edges by integrating transcription factor (TF) binding, evolutionarily conserved sequence motifs, gene expression, and chromatin modification data sets as input features. Applying these methods to Drosophila melanogaster, we predict ∼300,000 regulatory edges in a network of ∼600 TFs and 12,000 target genes. We validate our predictions using known regulatory interactions, gene functional annotations, tissue-specific expression, protein–protein interactions, and three-dimensional maps of chromosome conformation. We use the inferred network to identify putative functions for hundreds of previously uncharacterized genes, including many in nervous system development, which are independently confirmed based on their tissue-specific expression patterns. Last, we use the regulatory network to predict target gene expression levels as a function of TF expression, and find significantly higher predictive power for integrative networks than for motif or ChIP-based networks. Our work reveals the complementarity between physical evidence of regulatory interactions (TF binding, motif conservation) and functional evidence (coordinated expression or chromatin patterns) and demonstrates the power of data integration for network inference and studies of gene regulation at the systems level. PMID:22456606

Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Data Analysis and Visualization; nternational Research Training Group ``Visualization of Large and Unstructured Data Sets,'' University of Kaiserslautern, Germany; Computational Research Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA

2008-05-12

The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses of the complex gene regulatory networks controlling animal development. We present an integrated visualization and analysis framework that supports user-guided data clustering to aid exploration of these new complex datasets. The interplay of data visualization and clustering-based data classification leads to improved visualization and enables a more detailed analysis than previously possible. We discuss (i) integration of data clustering and visualization into one framework; (ii) application of data clustering to 3D gene expression data; (iii)more » evaluation of the number of clusters k in the context of 3D gene expression clustering; and (iv) improvement of overall analysis quality via dedicated post-processing of clustering results based on visualization. We discuss the use of this framework to objectively define spatial pattern boundaries and temporal profiles of genes and to analyze how mRNA patterns are controlled by their regulatory transcription factors.« less

TRACING CO-REGULATORY NETWORK DYNAMICS IN NOISY, SINGLE-CELL TRANSCRIPTOME TRAJECTORIES.

PubMed

Cordero, Pablo; Stuart, Joshua M

2017-01-01

The availability of gene expression data at the single cell level makes it possible to probe the molecular underpinnings of complex biological processes such as differentiation and oncogenesis. Promising new methods have emerged for reconstructing a progression 'trajectory' from static single-cell transcriptome measurements. However, it remains unclear how to adequately model the appreciable level of noise in these data to elucidate gene regulatory network rewiring. Here, we present a framework called Single Cell Inference of MorphIng Trajectories and their Associated Regulation (SCIMITAR) that infers progressions from static single-cell transcriptomes by employing a continuous parametrization of Gaussian mixtures in high-dimensional curves. SCIMITAR yields rich models from the data that highlight genes with expression and co-expression patterns that are associated with the inferred progression. Further, SCIMITAR extracts regulatory states from the implicated trajectory-evolvingco-expression networks. We benchmark the method on simulated data to show that it yields accurate cell ordering and gene network inferences. Applied to the interpretation of a single-cell human fetal neuron dataset, SCIMITAR finds progression-associated genes in cornerstone neural differentiation pathways missed by standard differential expression tests. Finally, by leveraging the rewiring of gene-gene co-expression relations across the progression, the method reveals the rise and fall of co-regulatory states and trajectory-dependent gene modules. These analyses implicate new transcription factors in neural differentiation including putative co-factors for the multi-functional NFAT pathway.

Three-Dimensional mRNA Measurements Reveal Minimal Regional Heterogeneity in Esophageal Squamous Cell Carcinoma

PubMed Central

Yan, Wusheng; Shih, Joanna; Rodriguez-Canales, Jaime; Tangrea, Michael A.; Player, Audrey; Diao, Lixia; Hu, Nan; Goldstein, Alisa M.; Wang, Jing; Taylor, Philip R.; Lippman, Scott M.; Wistuba, Ignacio I.; Emmert-Buck, Michael R.; Erickson, Heidi S.

2014-01-01

The classic tumor clonal evolution theory postulates that cancers change over time to produce unique molecular subclones within a parent neoplasm, presumably including regional differences in gene expression. More recently, however, this notion has been challenged by studies showing that tumors maintain a relatively stable transcript profile. To examine these competing hypotheses, we microdissected discrete subregions containing approximately 3000 to 8000 cells (500 to 1500 μm in diameter) from ex vivo esophageal squamous cell carcinoma (ESCC) specimens and analyzed transcriptomes throughout three-dimensional tumor space. Overall mRNA profiles were highly similar in all 59 intratumor comparisons, in distinct contrast to the markedly different global expression patterns observed in other dissected cell populations. For example, normal esophageal basal cells contained 1918 and 624 differentially expressed genes at a greater than twofold level (95% confidence level of <5% false positives), compared with normal differentiated esophageal cells and ESCC, respectively. In contrast, intratumor regions had only zero to four gene changes at a greater than twofold level, with most tumor comparisons showing none. The present data indicate that, when analyzed using a standard array-based method at this level of histological resolution, ESCC contains little regional mRNA heterogeneity. PMID:23219752

Pathway-based factor analysis of gene expression data produces highly heritable phenotypes that associate with age.

PubMed

Anand Brown, Andrew; Ding, Zhihao; Viñuela, Ana; Glass, Dan; Parts, Leopold; Spector, Tim; Winn, John; Durbin, Richard

2015-03-09

Statistical factor analysis methods have previously been used to remove noise components from high-dimensional data prior to genetic association mapping and, in a guided fashion, to summarize biologically relevant sources of variation. Here, we show how the derived factors summarizing pathway expression can be used to analyze the relationships between expression, heritability, and aging. We used skin gene expression data from 647 twins from the MuTHER Consortium and applied factor analysis to concisely summarize patterns of gene expression to remove broad confounding influences and to produce concise pathway-level phenotypes. We derived 930 "pathway phenotypes" that summarized patterns of variation across 186 KEGG pathways (five phenotypes per pathway). We identified 69 significant associations of age with phenotype from 57 distinct KEGG pathways at a stringent Bonferroni threshold ([Formula: see text]). These phenotypes are more heritable ([Formula: see text]) than gene expression levels. On average, expression levels of 16% of genes within these pathways are associated with age. Several significant pathways relate to metabolizing sugars and fatty acids; others relate to insulin signaling. We have demonstrated that factor analysis methods combined with biological knowledge can produce more reliable phenotypes with less stochastic noise than the individual gene expression levels, which increases our power to discover biologically relevant associations. These phenotypes could also be applied to discover associations with other environmental factors. Copyright © 2015 Brown et al.

Pathway-Based Factor Analysis of Gene Expression Data Produces Highly Heritable Phenotypes That Associate with Age

PubMed Central

Anand Brown, Andrew; Ding, Zhihao; Viñuela, Ana; Glass, Dan; Parts, Leopold; Spector, Tim; Winn, John; Durbin, Richard

2015-01-01

Statistical factor analysis methods have previously been used to remove noise components from high-dimensional data prior to genetic association mapping and, in a guided fashion, to summarize biologically relevant sources of variation. Here, we show how the derived factors summarizing pathway expression can be used to analyze the relationships between expression, heritability, and aging. We used skin gene expression data from 647 twins from the MuTHER Consortium and applied factor analysis to concisely summarize patterns of gene expression to remove broad confounding influences and to produce concise pathway-level phenotypes. We derived 930 “pathway phenotypes” that summarized patterns of variation across 186 KEGG pathways (five phenotypes per pathway). We identified 69 significant associations of age with phenotype from 57 distinct KEGG pathways at a stringent Bonferroni threshold (P<5.38×10−5). These phenotypes are more heritable (h2=0.32) than gene expression levels. On average, expression levels of 16% of genes within these pathways are associated with age. Several significant pathways relate to metabolizing sugars and fatty acids; others relate to insulin signaling. We have demonstrated that factor analysis methods combined with biological knowledge can produce more reliable phenotypes with less stochastic noise than the individual gene expression levels, which increases our power to discover biologically relevant associations. These phenotypes could also be applied to discover associations with other environmental factors. PMID:25758824

Not just gene expression: 3D implications of chromatin modifications during sexual plant reproduction.

PubMed

Dukowic-Schulze, Stefanie; Liu, Chang; Chen, Changbin

2018-01-01

DNA methylation and histone modifications are epigenetic changes on a DNA molecule that alter the three-dimensional (3D) structure locally as well as globally, impacting chromatin looping and packaging on a larger scale. Epigenetic marks thus inform higher-order chromosome organization and placement in the nucleus. Conventional epigenetic marks are joined by chromatin modifiers like cohesins, condensins and membrane-anchoring complexes to support particularly 3D chromosome organization. The most popular consequences of epigenetic modifications are gene expression changes, but chromatin modifications have implications beyond this, particularly in actively dividing cells and during sexual reproduction. In this opinion paper, we will focus on epigenetic mechanisms and chromatin modifications during meiosis as part of plant sexual reproduction where 3D management of chromosomes and re-organization of chromatin are defining features and prime tasks in reproductive cells, not limited to modulating gene expression. Meiotic chromosome organization, pairing and synapsis of homologous chromosomes as well as distribution of meiotic double-strand breaks and resulting crossovers are presumably highly influenced by epigenetic mechanisms. Special mobile small RNAs have been described in anthers, where these so-called phasiRNAs seem to direct DNA methylation in meiotic cells. Intriguingly, many of the mentioned developmental processes make use of epigenetic changes and small RNAs in a manner other than gene expression changes. Widening our approaches and opening our mind to thinking three-dimensionally regarding epigenetics in plant development holds high promise for new discoveries and could give us a boost for further knowledge.

Statistical approach for selection of biologically informative genes.

PubMed

Das, Samarendra; Rai, Anil; Mishra, D C; Rai, Shesh N

2018-05-20

Selection of informative genes from high dimensional gene expression data has emerged as an important research area in genomics. Many gene selection techniques have been proposed so far are either based on relevancy or redundancy measure. Further, the performance of these techniques has been adjudged through post selection classification accuracy computed through a classifier using the selected genes. This performance metric may be statistically sound but may not be biologically relevant. A statistical approach, i.e. Boot-MRMR, was proposed based on a composite measure of maximum relevance and minimum redundancy, which is both statistically sound and biologically relevant for informative gene selection. For comparative evaluation of the proposed approach, we developed two biological sufficient criteria, i.e. Gene Set Enrichment with QTL (GSEQ) and biological similarity score based on Gene Ontology (GO). Further, a systematic and rigorous evaluation of the proposed technique with 12 existing gene selection techniques was carried out using five gene expression datasets. This evaluation was based on a broad spectrum of statistically sound (e.g. subject classification) and biological relevant (based on QTL and GO) criteria under a multiple criteria decision-making framework. The performance analysis showed that the proposed technique selects informative genes which are more biologically relevant. The proposed technique is also found to be quite competitive with the existing techniques with respect to subject classification and computational time. Our results also showed that under the multiple criteria decision-making setup, the proposed technique is best for informative gene selection over the available alternatives. Based on the proposed approach, an R Package, i.e. BootMRMR has been developed and available at https://cran.r-project.org/web/packages/BootMRMR. This study will provide a practical guide to select statistical techniques for selecting informative genes from high dimensional expression data for breeding and system biology studies. Published by Elsevier B.V.

Production of functional proteins: balance of shear stress and gravity

NASA Technical Reports Server (NTRS)

Kaysen, James Howard (Inventor); Hammond, Timothy Grant (Inventor); Goodwin, Thomas John (Inventor)

2004-01-01

The present invention provides a method for production of functional proteins including hormones by renal cells in a three dimensional co-culture process responsive to shear stress using a rotating wall vessel. Natural mixture of renal cells expresses the enzyme 1-a-hydroxylase which can be used to generate the active form of vitamin D: 1,25-diOH vitamin D3. The fibroblast cultures and co-culture of renal cortical cells express the gene for erythropoietin and secrete erythropoietin into the culture supernatant. Other shear stress response genes are also modulated by shear stress, such as toxin receptors megalin and cubulin (gp280). Also provided is a method of treating in-need individual with the functional proteins produced in a three dimensional co-culture process responsive to shear stress using a rotating wall vessel.

Production of functional proteins: balance of shear stress and gravity

NASA Technical Reports Server (NTRS)

Hammond, Timothy Grant (Inventor); Kaysen, James Howard (Inventor); Goodwin, Thomas John (Inventor)

2007-01-01

The present invention provides a method for production of functional proteins including hormones by renal cells in a three dimensional co-culture process responsive to shear stress using a rotating wall vessel. Natural mixture of renal cells expresses the enzyme 1-a-hydroxylase which can be used to generate the active form of vitamin D: 1,25-diOH vitamin D3. The fibroblast cultures and co-culture of renal cortical cells express the gene for erythropoietin and secrete erythropoietin into the culture supernatant. Other shear stress response genes are also modulated by shear stress, such as toxin receptors megalin and cubulin (gp280). Also provided is a method of treating in-need individual with the functional proteins produced in a three dimensional co-culture process responsive to shear stress using a rotating wall vessel.

Sample-space-based feature extraction and class preserving projection for gene expression data.

PubMed

Wang, Wenjun

2013-01-01

In order to overcome the problems of high computational complexity and serious matrix singularity for feature extraction using Principal Component Analysis (PCA) and Fisher's Linear Discrinimant Analysis (LDA) in high-dimensional data, sample-space-based feature extraction is presented, which transforms the computation procedure of feature extraction from gene space to sample space by representing the optimal transformation vector with the weighted sum of samples. The technique is used in the implementation of PCA, LDA, Class Preserving Projection (CPP) which is a new method for discriminant feature extraction proposed, and the experimental results on gene expression data demonstrate the effectiveness of the method.

Identification, Expression, and Functional Analysis of the Fructokinase Gene Family in Cassava.

PubMed

Yao, Yuan; Geng, Meng-Ting; Wu, Xiao-Hui; Sun, Chong; Wang, Yun-Lin; Chen, Xia; Shang, Lu; Lu, Xiao-Hua; Li, Zhan; Li, Rui-Mei; Fu, Shao-Ping; Duan, Rui-Jun; Liu, Jiao; Hu, Xin-Wen; Guo, Jian-Chun

2017-11-12

Fructokinase (FRK) proteins play important roles in catalyzing fructose phosphorylation and participate in the carbohydrate metabolism of storage organs in plants. To investigate the roles of FRKs in cassava tuber root development, seven FRK genes ( MeFRK1 - 7 ) were identified, and MeFRK1 - 6 were isolated. Phylogenetic analysis revealed that the MeFRK family genes can be divided into α ( MeFRK 1 , 2 , 6 , 7 ) and β ( MeFRK 3 , 4 , 5 ) groups. All the MeFRK proteins have typical conserved regions and substrate binding residues similar to those of the FRKs. The overall predicted three-dimensional structures of MeFRK1-6 were similar, folding into a catalytic domain and a β-sheet ''lid" region, forming a substrate binding cleft, which contains many residues involved in the binding to fructose. The gene and the predicted three-dimensional structures of MeFRK3 and MeFRK4 were the most similar. MeFRK1-6 displayed different expression patterns across different tissues, including leaves, stems, tuber roots, flowers, and fruits. In tuber roots, the expressions of MeFRK3 and MeFRK4 were much higher compared to those of the other genes. Notably, the expression of MeFRK3 and MeFRK4 as well as the enzymatic activity of FRK were higher at the initial and early expanding tuber stages and were lower at the later expanding and mature tuber stages. The FRK activity of MeFRK3 and MeFRK4 was identified by the functional complementation of triple mutant yeast cells that were unable to phosphorylate either glucose or fructose. The gene expression and enzymatic activity of MeFRK3 and MeFRK4 suggest that they might be the main enzymes in fructose phosphorylation for regulating the formation of tuber roots and starch accumulation at the tuber root initial and expanding stages.

Harnessing the complexity of gene expression data from cancer: from single gene to structural pathway methods

PubMed Central

2012-01-01

High-dimensional gene expression data provide a rich source of information because they capture the expression level of genes in dynamic states that reflect the biological functioning of a cell. For this reason, such data are suitable to reveal systems related properties inside a cell, e.g., in order to elucidate molecular mechanisms of complex diseases like breast or prostate cancer. However, this is not only strongly dependent on the sample size and the correlation structure of a data set, but also on the statistical hypotheses tested. Many different approaches have been developed over the years to analyze gene expression data to (I) identify changes in single genes, (II) identify changes in gene sets or pathways, and (III) identify changes in the correlation structure in pathways. In this paper, we review statistical methods for all three types of approaches, including subtypes, in the context of cancer data and provide links to software implementations and tools and address also the general problem of multiple hypotheses testing. Further, we provide recommendations for the selection of such analysis methods. Reviewers This article was reviewed by Arcady Mushegian, Byung-Soo Kim and Joel Bader. PMID:23227854

Combining laser microdissection and RNA-seq to chart the transcriptional landscape of fungal development

PubMed Central

2012-01-01

Background During sexual development, filamentous ascomycetes form complex, three-dimensional fruiting bodies for the protection and dispersal of sexual spores. Fruiting bodies contain a number of cell types not found in vegetative mycelium, and these morphological differences are thought to be mediated by changes in gene expression. However, little is known about the spatial distribution of gene expression in fungal development. Here, we used laser microdissection (LM) and RNA-seq to determine gene expression patterns in young fruiting bodies (protoperithecia) and non-reproductive mycelia of the ascomycete Sordaria macrospora. Results Quantitative analysis showed major differences in the gene expression patterns between protoperithecia and total mycelium. Among the genes strongly up-regulated in protoperithecia were the pheromone precursor genes ppg1 and ppg2. The up-regulation was confirmed by fluorescence microscopy of egfp expression under the control of ppg1 regulatory sequences. RNA-seq analysis of protoperithecia from the sterile mutant pro1 showed that many genes that are differentially regulated in these structures are under the genetic control of transcription factor PRO1. Conclusions We have generated transcriptional profiles of young fungal sexual structures using a combination of LM and RNA-seq. This allowed a high spatial resolution and sensitivity, and yielded a detailed picture of gene expression during development. Our data revealed significant differences in gene expression between protoperithecia and non-reproductive mycelia, and showed that the transcription factor PRO1 is involved in the regulation of many genes expressed specifically in sexual structures. The LM/RNA-seq approach will also be relevant to other eukaryotic systems in which multicellular development is investigated. PMID:23016559

Linking Advanced Visualization and MATLAB for the Analysis of 3D Gene Expression Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruebel, Oliver; Keranen, Soile V.E.; Biggin, Mark

Three-dimensional gene expression PointCloud data generated by the Berkeley Drosophila Transcription Network Project (BDTNP) provides quantitative information about the spatial and temporal expression of genes in early Drosophila embryos at cellular resolution. The BDTNP team visualizes and analyzes Point-Cloud data using the software application PointCloudXplore (PCX). To maximize the impact of novel, complex data sets, such as PointClouds, the data needs to be accessible to biologists and comprehensible to developers of analysis functions. We address this challenge by linking PCX and Matlab via a dedicated interface, thereby providing biologists seamless access to advanced data analysis functions and giving bioinformatics researchersmore » the opportunity to integrate their analysis directly into the visualization application. To demonstrate the usefulness of this approach, we computationally model parts of the expression pattern of the gene even skipped using a genetic algorithm implemented in Matlab and integrated into PCX via our Matlab interface.« less

Interleukin 1-beta upregulates brain-derived neurotrophic factor, neurotrophin 3 and neuropilin 2 gene expression and NGF production in annulus cells.

PubMed

Gruber, H E; Hoelscher, G L; Bethea, S; Hanley, E N

2012-11-01

The relationship between disc cells, nerves and pain production in the intervertebral disc is poorly understood. Neurotrophins, signaling molecules involved in the survival, differentiation and migration of neurons, and neurite outgrowth, are expressed in non-neuronal tissues including the disc. We hypothesized that three-dimensional exposure of human disc cells to the proinflammatory cytokine IL-1ß in vitro would elevate neurotrophin gene expression levels and production of nerve growth factor (NGF). Cells isolated from Thompson grade III and IV discs were cultured for 14 days under control conditions or with addition of 10(2) pM IL-1ß; mRNA was isolated and conditioned media assayed for NGF content. IL-1ß exposure in three-dimensional culture significantly increased expression of neurotrophin 3, brain-derived neurotrophic factor, and neuropilin 2 compared to controls. IL-1ß-exposed cells showed significantly increased NGF production compared to controls. Findings support our hypothesis, expand previous data concerning expression of neurotrophins, and provide the first documented expression of neurotrophin 3 and neuropilin 2. Our results have direct translational relevance, because they address the primary clinical issue of low back pain and open the possibility of novel analgesic therapies using specific small-molecular antagonists to neurotrophins.

Improved Sparse Multi-Class SVM and Its Application for Gene Selection in Cancer Classification

PubMed Central

Huang, Lingkang; Zhang, Hao Helen; Zeng, Zhao-Bang; Bushel, Pierre R.

2013-01-01

Background Microarray techniques provide promising tools for cancer diagnosis using gene expression profiles. However, molecular diagnosis based on high-throughput platforms presents great challenges due to the overwhelming number of variables versus the small sample size and the complex nature of multi-type tumors. Support vector machines (SVMs) have shown superior performance in cancer classification due to their ability to handle high dimensional low sample size data. The multi-class SVM algorithm of Crammer and Singer provides a natural framework for multi-class learning. Despite its effective performance, the procedure utilizes all variables without selection. In this paper, we propose to improve the procedure by imposing shrinkage penalties in learning to enforce solution sparsity. Results The original multi-class SVM of Crammer and Singer is effective for multi-class classification but does not conduct variable selection. We improved the method by introducing soft-thresholding type penalties to incorporate variable selection into multi-class classification for high dimensional data. The new methods were applied to simulated data and two cancer gene expression data sets. The results demonstrate that the new methods can select a small number of genes for building accurate multi-class classification rules. Furthermore, the important genes selected by the methods overlap significantly, suggesting general agreement among different variable selection schemes. Conclusions High accuracy and sparsity make the new methods attractive for cancer diagnostics with gene expression data and defining targets of therapeutic intervention. Availability: The source MATLAB code are available from http://math.arizona.edu/~hzhang/software.html. PMID:23966761

Three-dimensional Tissue Culture Based on Magnetic Cell Levitation

PubMed Central

Souza, Glauco R.; Molina, Jennifer R.; Raphael, Robert M.; Ozawa, Michael G.; Stark, Daniel J.; Levin, Carly S.; Bronk, Lawrence F.; Ananta, Jeyarama S.; Mandelin, Jami; Georgescu, Maria-Magdalena; Bankson, James A.; Gelovani, Juri G.

2015-01-01

Cell culture is an essential tool for drug discovery, tissue engineering, and stem cell research. Conventional tissue culture produces two-dimensional (2D) cell growth with gene expression, signaling, and morphology that can differ from those in vivo and thus compromise clinical relevancy1–5. Here we report a three-dimensional (3D) culture of cells based on magnetic levitation in the presence of hydrogels containing gold and magnetic iron oxide (MIO) nanoparticles plus filamentous bacteriophage. This methodology allows for control of cell mass geometry and guided, multicellular clustering of different cell types in co-culture through spatial variance of the magnetic field. Moreover, magnetic levitation of human glioblastoma cells demonstrates similar protein expression profiles to those observed in human tumor xenografts. Taken together, these results suggest levitated 3D culture with magnetized phage-based hydrogels more closely recapitulates in vivo protein expression and allows for long-term multi-cellular studies. PMID:20228788

Robust Learning of High-dimensional Biological Networks with Bayesian Networks

NASA Astrophysics Data System (ADS)

Nägele, Andreas; Dejori, Mathäus; Stetter, Martin

Structure learning of Bayesian networks applied to gene expression data has become a potentially useful method to estimate interactions between genes. However, the NP-hardness of Bayesian network structure learning renders the reconstruction of the full genetic network with thousands of genes unfeasible. Consequently, the maximal network size is usually restricted dramatically to a small set of genes (corresponding with variables in the Bayesian network). Although this feature reduction step makes structure learning computationally tractable, on the downside, the learned structure might be adversely affected due to the introduction of missing genes. Additionally, gene expression data are usually very sparse with respect to the number of samples, i.e., the number of genes is much greater than the number of different observations. Given these problems, learning robust network features from microarray data is a challenging task. This chapter presents several approaches tackling the robustness issue in order to obtain a more reliable estimation of learned network features.

Confident difference criterion: a new Bayesian differentially expressed gene selection algorithm with applications.

PubMed

Yu, Fang; Chen, Ming-Hui; Kuo, Lynn; Talbott, Heather; Davis, John S

2015-08-07

Recently, the Bayesian method becomes more popular for analyzing high dimensional gene expression data as it allows us to borrow information across different genes and provides powerful estimators for evaluating gene expression levels. It is crucial to develop a simple but efficient gene selection algorithm for detecting differentially expressed (DE) genes based on the Bayesian estimators. In this paper, by extending the two-criterion idea of Chen et al. (Chen M-H, Ibrahim JG, Chi Y-Y. A new class of mixture models for differential gene expression in DNA microarray data. J Stat Plan Inference. 2008;138:387-404), we propose two new gene selection algorithms for general Bayesian models and name these new methods as the confident difference criterion methods. One is based on the standardized differences between two mean expression values among genes; the other adds the differences between two variances to it. The proposed confident difference criterion methods first evaluate the posterior probability of a gene having different gene expressions between competitive samples and then declare a gene to be DE if the posterior probability is large. The theoretical connection between the proposed first method based on the means and the Bayes factor approach proposed by Yu et al. (Yu F, Chen M-H, Kuo L. Detecting differentially expressed genes using alibrated Bayes factors. Statistica Sinica. 2008;18:783-802) is established under the normal-normal-model with equal variances between two samples. The empirical performance of the proposed methods is examined and compared to those of several existing methods via several simulations. The results from these simulation studies show that the proposed confident difference criterion methods outperform the existing methods when comparing gene expressions across different conditions for both microarray studies and sequence-based high-throughput studies. A real dataset is used to further demonstrate the proposed methodology. In the real data application, the confident difference criterion methods successfully identified more clinically important DE genes than the other methods. The confident difference criterion method proposed in this paper provides a new efficient approach for both microarray studies and sequence-based high-throughput studies to identify differentially expressed genes.

Reverse engineering gene regulatory networks from measurement with missing values.

PubMed

Ogundijo, Oyetunji E; Elmas, Abdulkadir; Wang, Xiaodong

2016-12-01

Gene expression time series data are usually in the form of high-dimensional arrays. Unfortunately, the data may sometimes contain missing values: for either the expression values of some genes at some time points or the entire expression values of a single time point or some sets of consecutive time points. This significantly affects the performance of many algorithms for gene expression analysis that take as an input, the complete matrix of gene expression measurement. For instance, previous works have shown that gene regulatory interactions can be estimated from the complete matrix of gene expression measurement. Yet, till date, few algorithms have been proposed for the inference of gene regulatory network from gene expression data with missing values. We describe a nonlinear dynamic stochastic model for the evolution of gene expression. The model captures the structural, dynamical, and the nonlinear natures of the underlying biomolecular systems. We present point-based Gaussian approximation (PBGA) filters for joint state and parameter estimation of the system with one-step or two-step missing measurements . The PBGA filters use Gaussian approximation and various quadrature rules, such as the unscented transform (UT), the third-degree cubature rule and the central difference rule for computing the related posteriors. The proposed algorithm is evaluated with satisfying results for synthetic networks, in silico networks released as a part of the DREAM project, and the real biological network, the in vivo reverse engineering and modeling assessment (IRMA) network of yeast Saccharomyces cerevisiae . PBGA filters are proposed to elucidate the underlying gene regulatory network (GRN) from time series gene expression data that contain missing values. In our state-space model, we proposed a measurement model that incorporates the effect of the missing data points into the sequential algorithm. This approach produces a better inference of the model parameters and hence, more accurate prediction of the underlying GRN compared to when using the conventional Gaussian approximation (GA) filters ignoring the missing data points.

An Adaptive Genetic Association Test Using Double Kernel Machines.

PubMed

Zhan, Xiang; Epstein, Michael P; Ghosh, Debashis

2015-10-01

Recently, gene set-based approaches have become very popular in gene expression profiling studies for assessing how genetic variants are related to disease outcomes. Since most genes are not differentially expressed, existing pathway tests considering all genes within a pathway suffer from considerable noise and power loss. Moreover, for a differentially expressed pathway, it is of interest to select important genes that drive the effect of the pathway. In this article, we propose an adaptive association test using double kernel machines (DKM), which can both select important genes within the pathway as well as test for the overall genetic pathway effect. This DKM procedure first uses the garrote kernel machines (GKM) test for the purposes of subset selection and then the least squares kernel machine (LSKM) test for testing the effect of the subset of genes. An appealing feature of the kernel machine framework is that it can provide a flexible and unified method for multi-dimensional modeling of the genetic pathway effect allowing for both parametric and nonparametric components. This DKM approach is illustrated with application to simulated data as well as to data from a neuroimaging genetics study.

Upregulated epidermal growth factor receptor expression following near-infrared irradiation simulating solar radiation in a three-dimensional reconstructed human corneal epithelial tissue culture model

PubMed Central

Tanaka, Yohei; Nakayama, Jun

2016-01-01

Background and objective Humans are increasingly exposed to near-infrared (NIR) radiation from both natural (eg, solar) and artificial (eg, electrical appliances) sources. Although the biological effects of sun and ultraviolet (UV) exposure have been extensively investigated, the biological effect of NIR radiation is still unclear. We previously reported that NIR as well as UV induces photoaging and standard UV-blocking materials, such as sunglasses, do not sufficiently block NIR. The objective of this study was to investigate changes in gene expression in three-dimensional reconstructed corneal epithelial tissue culture exposed to broad-spectrum NIR irradiation to simulate solar NIR radiation that reaches human tissues. Materials and methods DNA microarray and quantitative real-time polymerase chain reaction analysis were used to assess gene expression levels in a three-dimensional reconstructed corneal epithelial model composed of normal human corneal epithelial cells exposed to water-filtered broad-spectrum NIR irradiation with a contact cooling (20°C). The water-filter allowed 1,000–1,800 nm wavelengths and excluded 1,400–1,500 nm wavelengths. Results A DNA microarray with >62,000 different probes showed 25 and 150 genes that were up- or downregulated by at least fourfold and twofold, respectively, after NIR irradiation. In particular, epidermal growth factor receptor (EGFR) was upregulated by 19.4-fold relative to control cells. Quantitative real-time polymerase chain reaction analysis revealed that two variants of EGFR in human corneal epithelial tissue were also significantly upregulated after five rounds of 10 J/cm2 irradiation (P<0.05). Conclusion We found that NIR irradiation induced the upregulated expression of EGFR in human corneal cells. Since over half of the solar energy reaching the Earth is in the NIR region, which cannot be adequately blocked by eyewear and thus can induce eye damage with intensive or long-term exposure, protection from both UV and NIR radiation may prevent changes in gene expression and in turn eye damage. PMID:27536083

MetNet: Software to Build and Model the Biogenetic Lattice of Arabidopsis

DOE PAGES

Wurtele, Eve Syrkin; Li, Jie; Diao, Lixia; ...

2003-01-01

MetNet (http://www.botany.iastate.edu/∼mash/metnetex/metabolicnetex.html) is publicly available software in development for analysis of genome-wide RNA, protein and metabolite profiling data. The software is designed to enable the biologist to visualize, statistically analyse and model a metabolic and regulatory network map of Arabidopsis , combined with gene expression profiling data. It contains a JAVA interface to an interactions database (MetNetDB) containing information on regulatory and metabolic interactions derived from a combination of web databases (TAIR, KEGG, BRENDA) and input from biologists in their area of expertise. FCModeler captures input from MetNetDB in a graphical form. Sub-networks can be identified and interpreted using simplemore » fuzzy cognitive maps. FCModeler is intended to develop and evaluate hypotheses, and provide a modelling framework for assessing the large amounts of data captured by high-throughput gene expression experiments. FCModeler and MetNetDB are currently being extended to three-dimensional virtual reality display. The MetNet map, together with gene expression data, can be viewed using multivariate graphics tools in GGobi linked with the data analytic tools in R. Users can highlight different parts of the metabolic network and see the relevant expression data highlighted in other data plots. Multi-dimensional expression data can be rotated through different dimensions. Statistical analysis can be computed alongside the visual. MetNet is designed to provide a framework for the formulation of testable hypotheses regarding the function of specific genes, and in the long term provide the basis for identification of metabolic and regulatory networks that control plant composition and development.« less

Identification of DNA-binding proteins that interact with the 5'-flanking region of the human D-amino acid oxidase gene by pull-down assay coupled with two-dimensional gel electrophoresis and mass spectrometry.

PubMed

Tran, Diem Hong; Shishido, Yuji; Chung, Seong Pil; Trinh, Huong Thi Thanh; Yorita, Kazuko; Sakai, Takashi; Fukui, Kiyoshi

2015-12-10

D-Amino acid oxidase (DAO) is a flavoenzyme that metabolizes D-amino acids and is expected to be a promising therapeutic target of schizophrenia and glioblastoma. The study of DNA-binding proteins has yielded much information in the regulation of transcription and other biological processes. However, proteins interacting with DAO gene have not been elucidated. Our assessment of human DAO promoter activity using luciferase reporter system indicated the 5'-flanking region of this gene (-4289 bp from transcription initiation site) has a regulatory sequence for gene expression, which is regulated by multi-protein complexes interacting with this region. By using pull-down assay coupled with two-dimensional gel electrophoresis and mass spectrometry, we identified six proteins binding to the 5'-flanking region of the human DAO gene (zinc finger C2HC domain-containing protein 1A; histidine-tRNA ligase, cytoplasmic; molybdenum cofactor biosynthesis protein; 60S ribosomal protein L37; calponin-1; calmodulin binding protein and heterogeneous nuclear ribonucleoprotein A2/B1). These preliminary results will contribute to the advance in the understanding of the potential factors associated with the regulatory mechanism of DAO expression. Copyright © 2015 Elsevier B.V. All rights reserved.

Genome-wide analysis and expression profiling suggest diverse roles of GH3 genes during development and abiotic stress responses in legumes

PubMed Central

Singh, Vikash K.; Jain, Mukesh; Garg, Rohini

2014-01-01

Growth hormone auxin regulates various cellular processes by altering the expression of diverse genes in plants. Among various auxin-responsive genes, GH3 genes maintain endogenous auxin homeostasis by conjugating excess of auxin with amino acids. GH3 genes have been characterized in many plant species, but not in legumes. In the present work, we identified members of GH3 gene family and analyzed their chromosomal distribution, gene structure, gene duplication and phylogenetic analysis in different legumes, including chickpea, soybean, Medicago, and Lotus. A comprehensive expression analysis in different vegetative and reproductive tissues/stages revealed that many of GH3 genes were expressed in a tissue-specific manner. Notably, chickpea CaGH3-3, soybean GmGH3-8 and -25, and Lotus LjGH3-4, -5, -9 and -18 genes were up-regulated in root, indicating their putative role in root development. In addition, chickpea CaGH3-1 and -7, and Medicago MtGH3-7, -8, and -9 were found to be highly induced under drought and/or salt stresses, suggesting their role in abiotic stress responses. We also observed the examples of differential expression pattern of duplicated GH3 genes in soybean, indicating their functional diversification. Furthermore, analyses of three-dimensional structures, active site residues and ligand preferences provided molecular insights into function of GH3 genes in legumes. The analysis presented here would help in investigation of precise function of GH3 genes in legumes during development and stress conditions. PMID:25642236

Analysis of dofA, a fruA-dependent developmental gene, and its homologue, dofB, in Myxococcus xanthus.

PubMed

Horiuchi, Takayuki; Akiyama, Takuya; Inouye, Sumiko; Komano, Teruya

2002-12-01

The developmentally regulated gene dofA, identified from pulse-labeling experiments by two-dimensional gel electrophoresis, and its homologue, dofB, were cloned and characterized in Myxococcus xanthus. Deletion of dofA and dofB did not affect the vegetative growth and development of M. xanthus. dofA was specifically expressed during development, while dofB expression was observed during vegetative growth and development. The dofA-lacZ fusion was introduced into a fruA mutant and A, B, C, D, and E extracellular signal mutants. The pattern of dofA expression in the C signal mutant was similar to that of the wild-type strain, while dofA expression was not detected in the fruA mutant. These results are consistent with those of the pulse-labeling experiments. dofA expression was reduced in A and E signal mutants, whereas dofA expression was delayed in B and D signal mutants. The patterns of expression of the dofA gene in the fruA mutant and the five signal mutants are strikingly similar to that of the tps gene, which encodes protein S, a major component of the outer surface of the myxospore; this result suggests that the dofA and tps genes are similarly regulated. The involvement of a highly GC-rich inverted repeat sequence (underlined), CGGCCCCCGATTCGTCGGGGGCCG, in developmentally regulated dofA expression is suggested.

Decreased expression of the stress protein HSP70 is an early event in murine erythroleukemic cell differentiation.

PubMed Central

Hensold, J O; Housman, D E

1988-01-01

Two-dimensional protein gels were used to systematically assess changes in gene expression in Friend erythroleukemia cells after exposure to inducers of differentiation. A rapid decrease in expression of the stress protein HSP70 was observed after exposure to inducers. The kinetics of this change suggest that it may be related to the cellular events that regulate the onset of differentiation. Images PMID:3164440

Analytical approximations for spatial stochastic gene expression in single cells and tissues

PubMed Central

Smith, Stephen; Cianci, Claudia; Grima, Ramon

2016-01-01

Gene expression occurs in an environment in which both stochastic and diffusive effects are significant. Spatial stochastic simulations are computationally expensive compared with their deterministic counterparts, and hence little is currently known of the significance of intrinsic noise in a spatial setting. Starting from the reaction–diffusion master equation (RDME) describing stochastic reaction–diffusion processes, we here derive expressions for the approximate steady-state mean concentrations which are explicit functions of the dimensionality of space, rate constants and diffusion coefficients. The expressions have a simple closed form when the system consists of one effective species. These formulae show that, even for spatially homogeneous systems, mean concentrations can depend on diffusion coefficients: this contradicts the predictions of deterministic reaction–diffusion processes, thus highlighting the importance of intrinsic noise. We confirm our theory by comparison with stochastic simulations, using the RDME and Brownian dynamics, of two models of stochastic and spatial gene expression in single cells and tissues. PMID:27146686

Pairwise gene GO-based measures for biclustering of high-dimensional expression data.

PubMed

Nepomuceno, Juan A; Troncoso, Alicia; Nepomuceno-Chamorro, Isabel A; Aguilar-Ruiz, Jesús S

2018-01-01

Biclustering algorithms search for groups of genes that share the same behavior under a subset of samples in gene expression data. Nowadays, the biological knowledge available in public repositories can be used to drive these algorithms to find biclusters composed of groups of genes functionally coherent. On the other hand, a distance among genes can be defined according to their information stored in Gene Ontology (GO). Gene pairwise GO semantic similarity measures report a value for each pair of genes which establishes their functional similarity. A scatter search-based algorithm that optimizes a merit function that integrates GO information is studied in this paper. This merit function uses a term that addresses the information through a GO measure. The effect of two possible different gene pairwise GO measures on the performance of the algorithm is analyzed. Firstly, three well known yeast datasets with approximately one thousand of genes are studied. Secondly, a group of human datasets related to clinical data of cancer is also explored by the algorithm. Most of these data are high-dimensional datasets composed of a huge number of genes. The resultant biclusters reveal groups of genes linked by a same functionality when the search procedure is driven by one of the proposed GO measures. Furthermore, a qualitative biological study of a group of biclusters show their relevance from a cancer disease perspective. It can be concluded that the integration of biological information improves the performance of the biclustering process. The two different GO measures studied show an improvement in the results obtained for the yeast dataset. However, if datasets are composed of a huge number of genes, only one of them really improves the algorithm performance. This second case constitutes a clear option to explore interesting datasets from a clinical point of view.

The Effect of Hydrostatic Pressure on Three-Dimensional Chondroinduction of Human Adipose–Derived Stem Cells

PubMed Central

Mizuno, Shuichi; Murphy, George F.; Orgill, Dennis P.

2009-01-01

Background The optimal production of three-dimensional cartilage in vitro requires both inductive factors and specified culture conditions (e.g., hydrostatic pressure [HP], gas concentration, and nutrient supply) to promote cell viability and maintain phenotype. In this study, we optimized the conditions for human cartilage induction using human adipose–derived stem cells (ASCs), collagen scaffolds, and cyclic HP treatment. Methods Human ASCs underwent primary culture and three passages before being seeded into collagen scaffolds. These constructs were incubated for 1 week in an automated bioreactor using cyclic HP at 0–0.5 MPa, 0.5 Hz, and compared to constructs exposed to atmospheric pressure. In both groups, chondrogenic differentiation medium including transforming growth factor-β1 was employed. One, 2, 3, and 4 weeks after incubation, the cell constructs were harvested for histological, immunohistochemical, and gene expression evaluation. Results In histological and immunohistochemical analyzes, pericellular and extracellular metachromatic matrix was observed in both groups and increased over 4 weeks, but accumulated at a higher rate in the HP group. Cell number was maintained in the HP group over 4 weeks but decreased after 2 weeks in the atmospheric pressure group. Chondrogenic-specific gene expression of type II and X collagen, aggrecan, and SRY-box9 was increased in the HP group especially after 2 weeks. Conclusion Our results demonstrate chondrogenic differentiation of ASCs in a three-dimensional collagen scaffolds with treatment of a cyclic HP. Cyclic HP was effective in enhancing accumulation of extracellular matrix and expression of genes indicative of chondrogenic differentiation. PMID:19290804

Microarray analysis of genes differentially expressed in HepG2 cells cultured in simulated microgravity: preliminary report

NASA Technical Reports Server (NTRS)

Khaoustov, V. I.; Risin, D.; Pellis, N. R.; Yoffe, B.; McIntire, L. V. (Principal Investigator)

2001-01-01

Developed at NASA, the rotary cell culture system (RCCS) allows the creation of unique microgravity environment of low shear force, high-mass transfer, and enables three-dimensional (3D) cell culture of dissimilar cell types. Recently we demonstrated that a simulated microgravity is conducive for maintaining long-term cultures of functional hepatocytes and promote 3D cell assembly. Using deoxyribonucleic acid (DNA) microarray technology, it is now possible to measure the levels of thousands of different messenger ribonucleic acids (mRNAs) in a single hybridization step. This technique is particularly powerful for comparing gene expression in the same tissue under different environmental conditions. The aim of this research was to analyze gene expression of hepatoblastoma cell line (HepG2) during early stage of 3D-cell assembly in simulated microgravity. For this, mRNA from HepG2 cultured in the RCCS was analyzed by deoxyribonucleic acid microarray. Analyses of HepG2 mRNA by using 6K glass DNA microarray revealed changes in expression of 95 genes (overexpression of 85 genes and downregulation of 10 genes). Our preliminary results indicated that simulated microgravity modifies the expression of several genes and that microarray technology may provide new understanding of the fundamental biological questions of how gravity affects the development and function of individual cells.

Extracellular matrix influence in Streptococcus mutans gene expression in a cariogenic biofilm.

PubMed

Florez Salamanca, E J; Klein, M I

2018-04-01

Caries etiology is biofilm-diet-dependent. Biofilms are highly dynamic and structured microbial communities enmeshed in a three-dimensional extracellular matrix. The study evaluated the expression dynamics of Streptococcus mutans genes associated with exopolysaccharides (EPS) (gtfBCD, gbpB, dexA), lipoteichoic acids (LTA) (dltABCD, SMU_775c) and extracellular DNA (eDNA) (lytST, lrgAB, ccpA) during matrix development within a mixed-species biofilm of S. mutans, Actinomyces naeslundii and Streptococcus gordonii. Mixed-species biofilms using S. mutans strains UA159 or ΔgtfB formed on saliva-coated hydroxyapatite discs were submitted to a nutritional challenge (providing an abundance of sucrose and starch). Biofilms were removed at eight developmental stages for gene expression analysis by quantitative polymerase chain reaction. The pH of spent culture media remained acidic throughout the experimental periods, being lower after sucrose and starch exposure. All genes were expressed at all biofilm developmental phases. EPS- and LTA-associated genes had a similar expression profile for both biofilms, presenting lower levels of expression at 67, 91 and 115 hours and a peak of expression at 55 hours, but having distinct expression magnitudes, with lower values for ΔgtfB (eg, fold-difference of ~382 for gtfC and ~16 for dltB at 43 hours). The eDNA-associated genes presented different dynamics of expression between both strains. In UA159 biofilms lrgA and lrgB genes were highly expressed at 29 hours (which were ~13 and ~5.4 times vs ΔgtfB, respectively), whereas in ΔgtfB biofilms an inverse relationship between lytS and lrgA and lrgB expression was detected. Therefore, the deletion of gtfB influences dynamics and magnitude of expression of genes associated with matrix main components. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A new approach to enhance the performance of decision tree for classifying gene expression data.

PubMed

Hassan, Md; Kotagiri, Ramamohanarao

2013-12-20

Gene expression data classification is a challenging task due to the large dimensionality and very small number of samples. Decision tree is one of the popular machine learning approaches to address such classification problems. However, the existing decision tree algorithms use a single gene feature at each node to split the data into its child nodes and hence might suffer from poor performance specially when classifying gene expression dataset. By using a new decision tree algorithm where, each node of the tree consists of more than one gene, we enhance the classification performance of traditional decision tree classifiers. Our method selects suitable genes that are combined using a linear function to form a derived composite feature. To determine the structure of the tree we use the area under the Receiver Operating Characteristics curve (AUC). Experimental analysis demonstrates higher classification accuracy using the new decision tree compared to the other existing decision trees in literature. We experimentally compare the effect of our scheme against other well known decision tree techniques. Experiments show that our algorithm can substantially boost the classification performance of the decision tree.

Nested Expression Domains for Odorant Receptors in Zebrafish Olfactory Epithelium

NASA Astrophysics Data System (ADS)

Weth, Franco; Nadler, Walter; Korsching, Sigrun

1996-11-01

The mapping of high-dimensional olfactory stimuli onto the two-dimensional surface of the nasal sensory epithelium constitutes the first step in the neuronal encoding of olfactory input. We have used zebrafish as a model system to analyze the spatial distribution of odorant receptor molecules in the olfactory epithelium by quantitative in situ hybridization. To this end, we have cloned 10 very divergent zebrafish odorant receptor molecules by PCR. Individual genes are expressed in sparse olfactory receptor neurons. Analysis of the position of labeled cells in a simplified coordinate system revealed three concentric, albeit overlapping, expression domains for the four odorant receptors analyzed in detail. Such regionalized expression should result in a corresponding segregation of functional response properties. This might represent the first step of spatial encoding of olfactory input or be essential for the development of the olfactory system.

Improving Classification of Cancer and Mining Biomarkers from Gene Expression Profiles Using Hybrid Optimization Algorithms and Fuzzy Support Vector Machine

PubMed Central

Moteghaed, Niloofar Yousefi; Maghooli, Keivan; Garshasbi, Masoud

2018-01-01

Background: Gene expression data are characteristically high dimensional with a small sample size in contrast to the feature size and variability inherent in biological processes that contribute to difficulties in analysis. Selection of highly discriminative features decreases the computational cost and complexity of the classifier and improves its reliability for prediction of a new class of samples. Methods: The present study used hybrid particle swarm optimization and genetic algorithms for gene selection and a fuzzy support vector machine (SVM) as the classifier. Fuzzy logic is used to infer the importance of each sample in the training phase and decrease the outlier sensitivity of the system to increase the ability to generalize the classifier. A decision-tree algorithm was applied to the most frequent genes to develop a set of rules for each type of cancer. This improved the abilities of the algorithm by finding the best parameters for the classifier during the training phase without the need for trial-and-error by the user. The proposed approach was tested on four benchmark gene expression profiles. Results: Good results have been demonstrated for the proposed algorithm. The classification accuracy for leukemia data is 100%, for colon cancer is 96.67% and for breast cancer is 98%. The results show that the best kernel used in training the SVM classifier is the radial basis function. Conclusions: The experimental results show that the proposed algorithm can decrease the dimensionality of the dataset, determine the most informative gene subset, and improve classification accuracy using the optimal parameters of the classifier with no user interface. PMID:29535919

FastProject: a tool for low-dimensional analysis of single-cell RNA-Seq data.

PubMed

DeTomaso, David; Yosef, Nir

2016-08-23

A key challenge in the emerging field of single-cell RNA-Seq is to characterize phenotypic diversity between cells and visualize this information in an informative manner. A common technique when dealing with high-dimensional data is to project the data to 2 or 3 dimensions for visualization. However, there are a variety of methods to achieve this result and once projected, it can be difficult to ascribe biological significance to the observed features. Additionally, when analyzing single-cell data, the relationship between cells can be obscured by technical confounders such as variable gene capture rates. To aid in the analysis and interpretation of single-cell RNA-Seq data, we have developed FastProject, a software tool which analyzes a gene expression matrix and produces a dynamic output report in which two-dimensional projections of the data can be explored. Annotated gene sets (referred to as gene 'signatures') are incorporated so that features in the projections can be understood in relation to the biological processes they might represent. FastProject provides a novel method of scoring each cell against a gene signature so as to minimize the effect of missed transcripts as well as a method to rank signature-projection pairings so that meaningful associations can be quickly identified. Additionally, FastProject is written with a modular architecture and designed to serve as a platform for incorporating and comparing new projection methods and gene selection algorithms. Here we present FastProject, a software package for two-dimensional visualization of single cell data, which utilizes a plethora of projection methods and provides a way to systematically investigate the biological relevance of these low dimensional representations by incorporating domain knowledge.

Thymidine Kinase PET Reporter Gene Imaging of Cancer Cells In Vivo.

PubMed

McCracken, Melissa N

2018-01-01

Positron emission tomography (PET) is a three dimensional imaging modality that detects the accumulation of radiolabeled isotopes in vivo. Ectopic expression of a thymidine kinase reporter gene allows for the specific detection of reporter cells in vivo by imaging with the reporter specific probe. PET reporter imaging is sensitive, quantitative and can be scaled into larger tumors or animals with little to no tissue diffraction. Here, we describe how thymidine kinase PET reporter genes can be used to noninvasively image cancer cells in vivo.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aoyagi, Yasuyuki; Department of Genome Research and Clinical Application, Graduate School of Medicine, Chiba University, Chiba; Kuroda, Masayuki, E-mail: kurodam@faculty.chiba-u.jp

Adipose tissue is expected to provide a source of cells for protein replacement therapies via auto-transplantation. However, the conditioning of the environment surrounding the transplanted adipocytes for their long-term survival and protein secretion properties has not been established. We have recently developed a preparation procedure for preadipocytes, ceiling culture-derived proliferative adipocytes (ccdPAs), as a therapeutic gene vehicle suitable for stable gene product secretion. We herein report the results of our evaluation of using fibrin glue as a scaffold for the transplanted ccdPAs for the expression of a transduced gene in a three-dimensional culture system. The ccdPAs secreted the functional proteinmore » translated from an exogenously transduced gene, as well as physiological adipocyte proteins, and the long viability of ccdPAs (up to 84 days) was dependent on the fibrinogen concentrations. The ccdPAs spontaneously accumulated lipid droplets, and their expression levels of the transduced exogenous gene with its product were maintained for at least 56 days. The fibrinogen concentration modified the adipogenic differentiation of ccdPAs and their exogenous gene expression levels, and the levels of exogenously transduced gene expression at the different fibrinogen concentrations were dependent on the extent of adipogenic differentiation in the gel. These results indicate that fibrin glue helps to maintain the high adipogenic potential of cultured adipocytes after passaging in a 3D culture system, and suggests that once they are successfully implanted at the transplantation site, the cells exhibit increased expression of the transduced gene with adipogenic differentiation.« less

Angiogenesis-related gene expression analysis in celiac disease.

PubMed

Castellanos-Rubio, Ainara; Caja, Sergio; Irastorza, Iñaki; Fernandez-Jimenez, Nora; Plaza-Izurieta, Leticia; Vitoria, Juan Carlos; Maki, Markku; Lindfors, Katri; Bilbao, Jose Ramon

2012-05-01

Celiac disease (CD) involves disturbance of the small-bowel mucosal vascular network, and transglutaminase autoantibodies (TGA) have been related to angiogenesis disturbance, a complex phenomenon probably also influenced by common genetic variants in angiogenesis-related genes. A set of genes with "angiogenesis" GO term identified in a previous expression microarray experiment (SCG2, STAB1, TGFA, ANG, ERBB2, GNA13, PML, CASP8, ECGF1, JAG1, HIF1A, TNFSF13 and TGM2) was selected for genetic and functional studies. SNPs that showed a trend for association with CD in the first GWAS were genotyped in 555 patients and 541 controls. Gene expression of all genes was quantified in 15 pairs of intestinal biopsies (diagnosis vs. GFD) and in three-dimensional HUVEC and T84 cell cultures incubated with TGA-positive and negative serum. A regulatory SNP in TNFSF13 (rs11552708) is associated with CD (p = 0.01, OR = 0.7). Expression changes in biopsies pointed to TGM2 and PML as up-regulated antiangiogenic genes and to GNA13, TGFA, ERBB2 and SCG2 as down-regulated proangiogenic factors in CD. TGA seem to enhance TGM2 expression in both cell models, but PML expression was induced only in T84 enterocytes while GNA13 and ERBB2 were repressed in HUVEC endothelial cells, with several genes showing discordant effects in each model, highlighting the complexity of gene interactions in the pathogenesis of CD. Finally, cell culture models are useful tools to help dissect complex responses observed in human explants.

Unsupervised clustering of gene expression data points at hypoxia as possible trigger for metabolic syndrome.

PubMed

Ptitsyn, Andrey; Hulver, Matthew; Cefalu, William; York, David; Smith, Steven R

2006-12-19

Classification of large volumes of data produced in a microarray experiment allows for the extraction of important clues as to the nature of a disease. Using multi-dimensional unsupervised FOREL (FORmal ELement) algorithm we have re-analyzed three public datasets of skeletal muscle gene expression in connection with insulin resistance and type 2 diabetes (DM2). Our analysis revealed the major line of variation between expression profiles of normal, insulin resistant, and diabetic skeletal muscle. A cluster of most "metabolically sound" samples occupied one end of this line. The distance along this line coincided with the classic markers of diabetes risk, namely obesity and insulin resistance, but did not follow the accepted clinical diagnosis of DM2 as defined by the presence or absence of hyperglycemia. Genes implicated in this expression pattern are those controlling skeletal muscle fiber type and glycolytic metabolism. Additionally myoglobin and hemoglobin were upregulated and ribosomal genes deregulated in insulin resistant patients. Our findings are concordant with the changes seen in skeletal muscle with altitude hypoxia. This suggests that hypoxia and shift to glycolytic metabolism may also drive insulin resistance.

Functional, Anatomical, and Molecular Investigation of the Cardiac Conduction System and Arrhythmogenic Atrioventricular Ring Tissue in the Rat Heart

PubMed Central

Atkinson, Andrew J.; Logantha, Sunil Jit R. J.; Hao, Guoliang; Yanni, Joseph; Fedorenko, Olga; Sinha, Aditi; Gilbert, Stephen H.; Benson, Alan P.; Buckley, David L.; Anderson, Robert H.; Boyett, Mark R.; Dobrzynski, Halina

2013-01-01

Background The cardiac conduction system consists of the sinus node, nodal extensions, atrioventricular (AV) node, penetrating bundle, bundle branches, and Purkinje fibers. Node‐like AV ring tissue also exists at the AV junctions, and the right and left rings unite at the retroaortic node. The study aims were to (1) construct a 3‐dimensional anatomical model of the AV rings and retroaortic node, (2) map electrical activation in the right ring and study its action potential characteristics, and (3) examine gene expression in the right ring and retroaortic node. Methods and Results Three‐dimensional reconstruction (based on magnetic resonance imaging, histology, and immunohistochemistry) showed the extent and organization of the specialized tissues (eg, how the AV rings form the right and left nodal extensions into the AV node). Multiextracellular electrode array and microelectrode mapping of isolated right ring preparations revealed robust spontaneous activity with characteristic diastolic depolarization. Using laser microdissection gene expression measured at the mRNA level (using quantitative PCR) and protein level (using immunohistochemistry and Western blotting) showed that the right ring and retroaortic node, like the sinus node and AV node but, unlike ventricular muscle, had statistically significant higher expression of key transcription factors (including Tbx3, Msx2, and Id2) and ion channels (including HCN4, Cav3.1, Cav3.2, Kv1.5, SK1, Kir3.1, and Kir3.4) and lower expression of other key ion channels (Nav1.5 and Kir2.1). Conclusions The AV rings and retroaortic node possess gene expression profiles similar to that of the AV node. Ion channel expression and electrophysiological recordings show the AV rings could act as ectopic pacemakers and a source of atrial tachycardia. PMID:24356527

Nipbl and mediator cooperatively regulate gene expression to control limb development.

PubMed

Muto, Akihiko; Ikeda, Shingo; Lopez-Burks, Martha E; Kikuchi, Yutaka; Calof, Anne L; Lander, Arthur D; Schilling, Thomas F

2014-09-01

Haploinsufficiency for Nipbl, a cohesin loading protein, causes Cornelia de Lange Syndrome (CdLS), the most common "cohesinopathy". It has been proposed that the effects of Nipbl-haploinsufficiency result from disruption of long-range communication between DNA elements. Here we use zebrafish and mouse models of CdLS to examine how transcriptional changes caused by Nipbl deficiency give rise to limb defects, a common condition in individuals with CdLS. In the zebrafish pectoral fin (forelimb), knockdown of Nipbl expression led to size reductions and patterning defects that were preceded by dysregulated expression of key early limb development genes, including fgfs, shha, hand2 and multiple hox genes. In limb buds of Nipbl-haploinsufficient mice, transcriptome analysis revealed many similar gene expression changes, as well as altered expression of additional classes of genes that play roles in limb development. In both species, the pattern of dysregulation of hox-gene expression depended on genomic location within the Hox clusters. In view of studies suggesting that Nipbl colocalizes with the mediator complex, which facilitates enhancer-promoter communication, we also examined zebrafish deficient for the Med12 Mediator subunit, and found they resembled Nipbl-deficient fish in both morphology and gene expression. Moreover, combined partial reduction of both Nipbl and Med12 had a strongly synergistic effect, consistent with both molecules acting in a common pathway. In addition, three-dimensional fluorescent in situ hybridization revealed that Nipbl and Med12 are required to bring regions containing long-range enhancers into close proximity with the zebrafish hoxda cluster. These data demonstrate a crucial role for Nipbl in limb development, and support the view that its actions on multiple gene pathways result from its influence, together with Mediator, on regulation of long-range chromosomal interactions.

Analysis of dofA, a fruA-Dependent Developmental Gene, and Its Homologue, dofB, in Myxococcus xanthus

PubMed Central

Horiuchi, Takayuki; Akiyama, Takuya; Inouye, Sumiko; Komano, Teruya

2002-01-01

The developmentally regulated gene dofA, identified from pulse-labeling experiments by two-dimensional gel electrophoresis, and its homologue, dofB, were cloned and characterized in Myxococcus xanthus. Deletion of dofA and dofB did not affect the vegetative growth and development of M. xanthus. dofA was specifically expressed during development, while dofB expression was observed during vegetative growth and development. The dofA-lacZ fusion was introduced into a fruA mutant and A, B, C, D, and E extracellular signal mutants. The pattern of dofA expression in the C signal mutant was similar to that of the wild-type strain, while dofA expression was not detected in the fruA mutant. These results are consistent with those of the pulse-labeling experiments. dofA expression was reduced in A and E signal mutants, whereas dofA expression was delayed in B and D signal mutants. The patterns of expression of the dofA gene in the fruA mutant and the five signal mutants are strikingly similar to that of the tps gene, which encodes protein S, a major component of the outer surface of the myxospore; this result suggests that the dofA and tps genes are similarly regulated. The involvement of a highly GC-rich inverted repeat sequence (underlined), CGGCCCCCGATTCGTCGGGGGCCG, in developmentally regulated dofA expression is suggested. PMID:12446630

Gene Ranking of RNA-Seq Data via Discriminant Non-Negative Matrix Factorization.

PubMed

Jia, Zhilong; Zhang, Xiang; Guan, Naiyang; Bo, Xiaochen; Barnes, Michael R; Luo, Zhigang

2015-01-01

RNA-sequencing is rapidly becoming the method of choice for studying the full complexity of transcriptomes, however with increasing dimensionality, accurate gene ranking is becoming increasingly challenging. This paper proposes an accurate and sensitive gene ranking method that implements discriminant non-negative matrix factorization (DNMF) for RNA-seq data. To the best of our knowledge, this is the first work to explore the utility of DNMF for gene ranking. When incorporating Fisher's discriminant criteria and setting the reduced dimension as two, DNMF learns two factors to approximate the original gene expression data, abstracting the up-regulated or down-regulated metagene by using the sample label information. The first factor denotes all the genes' weights of two metagenes as the additive combination of all genes, while the second learned factor represents the expression values of two metagenes. In the gene ranking stage, all the genes are ranked as a descending sequence according to the differential values of the metagene weights. Leveraging the nature of NMF and Fisher's criterion, DNMF can robustly boost the gene ranking performance. The Area Under the Curve analysis of differential expression analysis on two benchmarking tests of four RNA-seq data sets with similar phenotypes showed that our proposed DNMF-based gene ranking method outperforms other widely used methods. Moreover, the Gene Set Enrichment Analysis also showed DNMF outweighs others. DNMF is also computationally efficient, substantially outperforming all other benchmarked methods. Consequently, we suggest DNMF is an effective method for the analysis of differential gene expression and gene ranking for RNA-seq data.

AucPR: an AUC-based approach using penalized regression for disease prediction with high-dimensional omics data.

PubMed

Yu, Wenbao; Park, Taesung

2014-01-01

It is common to get an optimal combination of markers for disease classification and prediction when multiple markers are available. Many approaches based on the area under the receiver operating characteristic curve (AUC) have been proposed. Existing works based on AUC in a high-dimensional context depend mainly on a non-parametric, smooth approximation of AUC, with no work using a parametric AUC-based approach, for high-dimensional data. We propose an AUC-based approach using penalized regression (AucPR), which is a parametric method used for obtaining a linear combination for maximizing the AUC. To obtain the AUC maximizer in a high-dimensional context, we transform a classical parametric AUC maximizer, which is used in a low-dimensional context, into a regression framework and thus, apply the penalization regression approach directly. Two kinds of penalization, lasso and elastic net, are considered. The parametric approach can avoid some of the difficulties of a conventional non-parametric AUC-based approach, such as the lack of an appropriate concave objective function and a prudent choice of the smoothing parameter. We apply the proposed AucPR for gene selection and classification using four real microarray and synthetic data. Through numerical studies, AucPR is shown to perform better than the penalized logistic regression and the nonparametric AUC-based method, in the sense of AUC and sensitivity for a given specificity, particularly when there are many correlated genes. We propose a powerful parametric and easily-implementable linear classifier AucPR, for gene selection and disease prediction for high-dimensional data. AucPR is recommended for its good prediction performance. Beside gene expression microarray data, AucPR can be applied to other types of high-dimensional omics data, such as miRNA and protein data.

Function Clustering Self-Organization Maps (FCSOMs) for mining differentially expressed genes in Drosophila and its correlation with the growth medium.

PubMed

Liu, L L; Liu, M J; Ma, M

2015-09-28

The central task of this study was to mine the gene-to-medium relationship. Adequate knowledge of this relationship could potentially improve the accuracy of differentially expressed gene mining. One of the approaches to differentially expressed gene mining uses conventional clustering algorithms to identify the gene-to-medium relationship. Compared to conventional clustering algorithms, self-organization maps (SOMs) identify the nonlinear aspects of the gene-to-medium relationships by mapping the input space into another higher dimensional feature space. However, SOMs are not suitable for huge datasets consisting of millions of samples. Therefore, a new computational model, the Function Clustering Self-Organization Maps (FCSOMs), was developed. FCSOMs take advantage of the theory of granular computing as well as advanced statistical learning methodologies, and are built specifically for each information granule (a function cluster of genes), which are intelligently partitioned by the clustering algorithm provided by the DAVID_6.7 software platform. However, only the gene functions, and not their expression values, are considered in the fuzzy clustering algorithm of DAVID. Compared to the clustering algorithm of DAVID, these experimental results show a marked improvement in the accuracy of classification with the application of FCSOMs. FCSOMs can handle huge datasets and their complex classification problems, as each FCSOM (modeled for each function cluster) can be easily parallelized.

An Adaptive Genetic Association Test Using Double Kernel Machines

PubMed Central

Zhan, Xiang; Epstein, Michael P.; Ghosh, Debashis

2014-01-01

Recently, gene set-based approaches have become very popular in gene expression profiling studies for assessing how genetic variants are related to disease outcomes. Since most genes are not differentially expressed, existing pathway tests considering all genes within a pathway suffer from considerable noise and power loss. Moreover, for a differentially expressed pathway, it is of interest to select important genes that drive the effect of the pathway. In this article, we propose an adaptive association test using double kernel machines (DKM), which can both select important genes within the pathway as well as test for the overall genetic pathway effect. This DKM procedure first uses the garrote kernel machines (GKM) test for the purposes of subset selection and then the least squares kernel machine (LSKM) test for testing the effect of the subset of genes. An appealing feature of the kernel machine framework is that it can provide a flexible and unified method for multi-dimensional modeling of the genetic pathway effect allowing for both parametric and nonparametric components. This DKM approach is illustrated with application to simulated data as well as to data from a neuroimaging genetics study. PMID:26640602

Variation analysis of the severe acute respiratory syndrome coronavirus putative non-structural protein 2 gene and construction of three-dimensional model.

PubMed

Lu, Jia-hai; Zhang, Ding-mei; Wang, Guo-ling; Guo, Zhong-min; Zhang, Chuan-hai; Tan, Bing-yan; Ouyang, Li-ping; Lin, Li; Liu, Yi-min; Chen, Wei-qing; Ling, Wen-hua; Yu, Xin-bing; Zhong, Nan-shan

2005-05-05

The rapid transmission and high mortality rate made severe acute respiratory syndrome (SARS) a global threat for which no efficacious therapy is available now. Without sufficient knowledge about the SARS coronavirus (SARS-CoV), it is impossible to define the candidate for the anti-SARS targets. The putative non-structural protein 2 (nsp2) (3CL(pro), following the nomenclature by Gao et al, also known as nsp5 in Snidjer et al) of SARS-CoV plays an important role in viral transcription and replication, and is an attractive target for anti-SARS drug development, so we carried on this study to have an insight into putative polymerase nsp2 of SARS-CoV Guangdong (GD) strain. The SARS-CoV strain was isolated from a SARS patient in Guangdong, China, and cultured in Vero E6 cells. The nsp2 gene was amplified by reverse transcription-polymerase chain reaction (RT-PCR) and cloned into eukaryotic expression vector pCI-neo (pCI-neo/nsp2). Then the recombinant eukaryotic expression vector pCI-neo/nsp2 was transfected into COS-7 cells using lipofectin reagent to express the nsp2 protein. The expressive protein of SARS-CoV nsp2 was analyzed by 7% sodium dodecylsulfate polyacrylamide gel electrophoresis (SDS-PAGE). The nucleotide sequence and protein sequence of GD nsp2 were compared with that of other SARS-CoV strains by nucleotide-nucleotide basic local alignment search tool (BLASTN) and protein-protein basic local alignment search tool (BLASTP) to investigate its variance trend during the transmission. The secondary structure of GD strain and that of other strains were predicted by Garnier-Osguthorpe-Robson (GOR) Secondary Structure Prediction. Three-dimensional-PSSM Protein Fold Recognition (Threading) Server was employed to construct the three-dimensional model of the nsp2 protein. The putative polymerase nsp2 gene of GD strain was amplified by RT-PCR. The eukaryotic expression vector (pCI-neo/nsp2) was constructed and expressed the protein in COS-7 cells successfully. The result of sequencing and sequence comparison with other SARS-CoV strains showed that nsp2 gene was relatively conservative during the transmission and total five base sites mutated in about 100 strains investigated, three of which in the early and middle phases caused synonymous mutation, and another two base sites variation in the late phase resulted in the amino acid substitutions and secondary structure changes. The three-dimensional structure of the nsp2 protein was successfully constructed. The results suggest that polymerase nsp2 is relatively stable during the phase of epidemic. The amino acid and secondary structure change may be important for viral infection. The fact that majority of single nucleotide variations (SNVs) are predicted to cause synonymous, as well as the result of low mutation rate of nsp2 gene in the epidemic variations, indicates that the nsp2 is conservative and could be a target for anti-SARS drugs. The three-dimensional structure result indicates that the nsp2 protein of GD strain is high homologous with 3CL(pro) of SARS-CoV urbani strain, 3CL(pro) of transmissible gastroenteritis virus and 3CL(pro) of human coronavirus 229E strain, which further suggests that nsp2 protein of GD strain possesses the activity of 3CL(pro).

Classification of ductal carcinoma in situ by gene expression profiling.

PubMed

Hannemann, Juliane; Velds, Arno; Halfwerk, Johannes B G; Kreike, Bas; Peterse, Johannes L; van de Vijver, Marc J

2006-01-01

Ductal carcinoma in situ (DCIS) is characterised by the intraductal proliferation of malignant epithelial cells. Several histological classification systems have been developed, but assessing the histological type/grade of DCIS lesions is still challenging, making treatment decisions based on these features difficult. To obtain insight in the molecular basis of the development of different types of DCIS and its progression to invasive breast cancer, we have studied differences in gene expression between different types of DCIS and between DCIS and invasive breast carcinomas. Gene expression profiling using microarray analysis has been performed on 40 in situ and 40 invasive breast cancer cases. DCIS cases were classified as well- (n = 6), intermediately (n = 18), and poorly (n = 14) differentiated type. Of the 40 invasive breast cancer samples, five samples were grade I, 11 samples were grade II, and 24 samples were grade III. Using two-dimensional hierarchical clustering, the basal-like type, ERB-B2 type, and the luminal-type tumours originally described for invasive breast cancer could also be identified in DCIS. Using supervised classification, we identified a gene expression classifier of 35 genes, which differed between DCIS and invasive breast cancer; a classifier of 43 genes could be identified separating between well- and poorly differentiated DCIS samples.

Classification of ductal carcinoma in situ by gene expression profiling

PubMed Central

Hannemann, Juliane; Velds, Arno; Halfwerk, Johannes BG; Kreike, Bas; Peterse, Johannes L; van de Vijver, Marc J

2006-01-01

Introduction Ductal carcinoma in situ (DCIS) is characterised by the intraductal proliferation of malignant epithelial cells. Several histological classification systems have been developed, but assessing the histological type/grade of DCIS lesions is still challenging, making treatment decisions based on these features difficult. To obtain insight in the molecular basis of the development of different types of DCIS and its progression to invasive breast cancer, we have studied differences in gene expression between different types of DCIS and between DCIS and invasive breast carcinomas. Methods Gene expression profiling using microarray analysis has been performed on 40 in situ and 40 invasive breast cancer cases. Results DCIS cases were classified as well- (n = 6), intermediately (n = 18), and poorly (n = 14) differentiated type. Of the 40 invasive breast cancer samples, five samples were grade I, 11 samples were grade II, and 24 samples were grade III. Using two-dimensional hierarchical clustering, the basal-like type, ERB-B2 type, and the luminal-type tumours originally described for invasive breast cancer could also be identified in DCIS. Conclusion Using supervised classification, we identified a gene expression classifier of 35 genes, which differed between DCIS and invasive breast cancer; a classifier of 43 genes could be identified separating between well- and poorly differentiated DCIS samples. PMID:17069663

Determination of multidrug resistance mechanisms in Clostridium perfringens type A isolates using RNA sequencing and 2D-electrophoresis.

PubMed

Ma, Yu-Hua; Ye, Gui-Sheng

2018-06-11

In this study, we screened differentially expressed genes in a multidrug-resistant isolate strain of Clostridium perfringens by RNA sequencing. We also separated and identified differentially expressed proteins (DEPs) in the isolate strain by two-dimensional electrophoresis (2-DE) and mass spectrometry (MS). The RNA sequencing results showed that, compared with the control strain, 1128 genes were differentially expressed in the isolate strain, and these included 227 up-regulated genes and 901 down-regulated genes. Bioinformatics analysis identified the following genes and gene categories that are potentially involved in multidrug resistance (MDR) in the isolate strain: drug transport, drug response, hydrolase activity, transmembrane transporter, transferase activity, amidase transmembrane transporter, efflux transmembrane transporter, bacterial chemotaxis, ABC transporter, and others. The results of the 2-DE showed that 70 proteins were differentially expressed in the isolate strain, 45 of which were up-regulated and 25 down-regulated. Twenty-seven DEPs were identified by MS and these included the following protein categories: ribosome, antimicrobial peptide resistance, and ABC transporter, all of which may be involved in MDR in the isolate strain of C. perfringens. The results provide reference data for further investigations on the drug resistant molecular mechanisms of C. perfringens.

Global Gene Expression Patterns and Somatic Mutations in Sporadic Intracranial Aneurysms.

PubMed

Li, Zhili; Tan, Haibin; Shi, Yi; Huang, Guangfu; Wang, Zhenyu; Liu, Ling; Yin, Cheng; Wang, Qi

2017-04-01

High-throughput sequencing technologies can expand our understanding of the pathologic basis of intracranial aneurysms (IAs). Our study was aimed to decipher the gene expression signature and genetic factors associated with IAs. We determined the gene expression levels of 3 cases of IAs by RNA sequencing. Bioinformatics analysis was conducted to identify the differentially expressed genes (DEGs) and uncover their biological function. In addition, whole genome sequencing was performed on an additional 6 cases of IAs to detect the potential somatic alterations in DEGs. Compared with the normal arterial tissue, 1709 genes were differentially expressed in IAs arterial tissue. The most significantly up-regulated gene and down-regulated gene, H19 and HIST1H3J, may be essential for tumorigenesis of IAs. Hub protein of IKBKG in protein-protein interaction network was probably involved in the inflammation process in aneurysms. Another 2 hub proteins, ACTB and MKI67IP, as well as up-regulated genes, might be abnormally activated in aneurysms and involved in the pathogenesis of IAs. Further whole genome sequencing and filtering yielded 4 candidate somatic single nucleotide variants including MUC3B, and BLM may be involved in the pathogenesis of IAs. Even though, our results do not support the hypothesis of somatic mutations occurred in the DEGs. Two-dimensional genomic data from transcriptome and whole genome sequencing indicated that no somatic mutations occurred in DEGs. In addition, 3 DEGs (IKBKG, ACTB, and MKI67IP) and 2 mutant genes (MUC3B and BLM) were essential in IAs. Copyright © 2017 Elsevier Inc. All rights reserved.

Network Reconstruction From High-Dimensional Ordinary Differential Equations.

PubMed

Chen, Shizhe; Shojaie, Ali; Witten, Daniela M

2017-01-01

We consider the task of learning a dynamical system from high-dimensional time-course data. For instance, we might wish to estimate a gene regulatory network from gene expression data measured at discrete time points. We model the dynamical system nonparametrically as a system of additive ordinary differential equations. Most existing methods for parameter estimation in ordinary differential equations estimate the derivatives from noisy observations. This is known to be challenging and inefficient. We propose a novel approach that does not involve derivative estimation. We show that the proposed method can consistently recover the true network structure even in high dimensions, and we demonstrate empirical improvement over competing approaches. Supplementary materials for this article are available online.

Three-dimensional spheroid culture promotes odonto/osteoblastic differentiation of dental pulp cells.

PubMed

Yamamoto, Mioko; Kawashima, Nobuyuki; Takashino, Nami; Koizumi, Yu; Takimoto, Koyo; Suzuki, Noriyuki; Saito, Masahiro; Suda, Hideaki

2014-03-01

Three-dimensional (3D) spheroid culture is a method for creating 3D aggregations of cells and their extracellular matrix without a scaffold mimicking the actual tissues. The aim of this study was to evaluate the effects of 3D spheroid culture on the phenotype of immortalized mouse dental papilla cells (MDPs) that have the ability to differentiate into odontoblasts. We cultured MDPs for 1, 3, 7, and 14 days in 96-well low-attachment culture plates for 3D spheroid culture or flat-bottomed plates for two-dimensional (2D) monolayer culture. Cell proliferation and apoptosis were detected by immunohistochemical staining of Ki67 and cleaved caspase-3, respectively. Hypoxia was measured by the hypoxia probe LOX-1. Odonto/osteoblastic differentiation marker gene expression was evaluated by quantitative PCR. We also determined mineralized nodule formation, alkaline phosphatase (ALP) activity, and dentine matrix protein-1 (DMP1) expression. Vinculin and integrin signalling-related proteins were detected immunohistochemically. Odonto/osteoblastic marker gene expression and mineralized nodule formation were significantly up-regulated in 3D spheroid-cultured MDPs compared with those in 2D monolayer-cultured MDPs (p<0.05). Histologically, 3D spheroid colonies consisted of two compartments: a cell-dense peripheral zone and cell-sparse core zone. Proliferating cells with high ALP activity and DMP1 expression were found mainly in the peripheral zone that also showed strong expression of vinculin and integrin signalling-related proteins. In contrast, apoptotic and hypoxic cells were detected in the core zone. 3D spheroid culture promotes odonto/osteoblastic differentiation of MDPs, which may be mediated by integrin signalling. Copyright © 2013 Elsevier Ltd. All rights reserved.

The gene road to royalty--differential expression of hydroxylating genes in the mandibular glands of the honeybee.

PubMed

Malka, Osnat; Karunker, Iris; Yeheskel, Adva; Morin, Shai; Hefetz, Abraham

2009-10-01

The advances in honeybee sociogenomics have paved the way for the study of social communication processes at the gene level, in particular the expression of caste-specific pheromones. The queen honeybee mandibular pheromone provides an excellent model system, in that biosynthesis of the hydroxylating fatty acid caste-specific pheromone appears to be reduced to a single chemical hydroxylation step of stearic acid. Queens are typified by omega-1-hydroxylation, as opposed to the worker-typical omega-hydroxylation. We hypothesized that this bifurcation is the consequence of differential expression of caste-specific genes that code for fatty acid-hydroxylating enzymes from the cytochrome P450 (CYP) family. Bioinformatics studies disclosed two candidate proteins CYP4AA1 and CYP18A1. We thus investigated the expression of these genes in the mandibular glands of queens, and of queenright (QR) and queenless (QL) workers. The real-time PCR results revealed that CYP4AA1 (omega-hydroxylation) was expressed at high levels in both QR and QL workers, whereas in queens its expression was negligible. The expression of CYP18A1 (omega-1-hydroxylation), on the other hand, was high in the queen's glands and negligible in those of QR workers. In QL workers, however, the expression of CYP18A1 was considerably elevated and significantly greater than in QR workers. Three-dimensional structural models constructed for these enzymes demonstrate differences in the active site between CYP18A1 and CYP4AA1, in line with their differential catalytic specificity. The fact that queen pheromone plasticity can be tracked all the way to gene expression provides a new insight into the process of caste differentiation and the accompanying social communication.

Geometry of the Gene Expression Space of Individual Cells

PubMed Central

Korem, Yael; Szekely, Pablo; Hart, Yuval; Sheftel, Hila; Hausser, Jean; Mayo, Avi; Rothenberg, Michael E.; Kalisky, Tomer; Alon, Uri

2015-01-01

There is a revolution in the ability to analyze gene expression of single cells in a tissue. To understand this data we must comprehend how cells are distributed in a high-dimensional gene expression space. One open question is whether cell types form discrete clusters or whether gene expression forms a continuum of states. If such a continuum exists, what is its geometry? Recent theory on evolutionary trade-offs suggests that cells that need to perform multiple tasks are arranged in a polygon or polyhedron (line, triangle, tetrahedron and so on, generally called polytopes) in gene expression space, whose vertices are the expression profiles optimal for each task. Here, we analyze single-cell data from human and mouse tissues profiled using a variety of single-cell technologies. We fit the data to shapes with different numbers of vertices, compute their statistical significance, and infer their tasks. We find cases in which single cells fill out a continuum of expression states within a polyhedron. This occurs in intestinal progenitor cells, which fill out a tetrahedron in gene expression space. The four vertices of this tetrahedron are each enriched with genes for a specific task related to stemness and early differentiation. A polyhedral continuum of states is also found in spleen dendritic cells, known to perform multiple immune tasks: cells fill out a tetrahedron whose vertices correspond to key tasks related to maturation, pathogen sensing and communication with lymphocytes. A mixture of continuum-like distributions and discrete clusters is found in other cell types, including bone marrow and differentiated intestinal crypt cells. This approach can be used to understand the geometry and biological tasks of a wide range of single-cell datasets. The present results suggest that the concept of cell type may be expanded. In addition to discreet clusters in gene-expression space, we suggest a new possibility: a continuum of states within a polyhedron, in which the vertices represent specialists at key tasks. PMID:26161936

GLO-Roots: an imaging platform enabling multidimensional characterization of soil-grown root systems

PubMed Central

Rellán-Álvarez, Rubén; Lobet, Guillaume; Lindner, Heike; Pradier, Pierre-Luc; Sebastian, Jose; Yee, Muh-Ching; Geng, Yu; Trontin, Charlotte; LaRue, Therese; Schrager-Lavelle, Amanda; Haney, Cara H; Nieu, Rita; Maloof, Julin; Vogel, John P; Dinneny, José R

2015-01-01

Root systems develop different root types that individually sense cues from their local environment and integrate this information with systemic signals. This complex multi-dimensional amalgam of inputs enables continuous adjustment of root growth rates, direction, and metabolic activity that define a dynamic physical network. Current methods for analyzing root biology balance physiological relevance with imaging capability. To bridge this divide, we developed an integrated-imaging system called Growth and Luminescence Observatory for Roots (GLO-Roots) that uses luminescence-based reporters to enable studies of root architecture and gene expression patterns in soil-grown, light-shielded roots. We have developed image analysis algorithms that allow the spatial integration of soil properties, gene expression, and root system architecture traits. We propose GLO-Roots as a system that has great utility in presenting environmental stimuli to roots in ways that evoke natural adaptive responses and in providing tools for studying the multi-dimensional nature of such processes. DOI: http://dx.doi.org/10.7554/eLife.07597.001 PMID:26287479

Does CTCF mediate between nuclear organization and gene expression?

PubMed

Ohlsson, Rolf; Lobanenkov, Victor; Klenova, Elena

2010-01-01

The multifunctional zinc-finger protein CCCTC-binding factor (CTCF) is a very strong candidate for the role of coordinating the expression level of coding sequences with their three-dimensional position in the nucleus, apparently responding to a "code" in the DNA itself. Dynamic interactions between chromatin fibers in the context of nuclear architecture have been implicated in various aspects of genome functions. However, the molecular basis of these interactions still remains elusive and is a subject of intense debate. Here we discuss the nature of CTCF-DNA interactions, the CTCF-binding specificity to its binding sites and the relationship between CTCF and chromatin, and we examine data linking CTCF with gene regulation in the three-dimensional nuclear space. We discuss why these features render CTCF a very strong candidate for the role and propose a unifying model, the "CTCF code," explaining the mechanistic basis of how the information encrypted in DNA may be interpreted by CTCF into diverse nuclear functions.

Osteogenic potency of a 3-dimensional scaffold-free bonelike sphere of periodontal ligament stem cells in vitro.

PubMed

Singhatanadgit, Weerachai; Varodomrujiranon, Manatsanan

2013-12-01

The present study aimed to investigate the osteogenic potency of scaffold-free 3-dimensional (3D) spheres of periodontal ligament stem cells (PDLSCs). The osteogenic potency of PDLSC spheres was determined by the ability to form mineralization and to express key osteogenesis-associated genes. The alkaline phosphatase (ALP) activity and the protein content of PDLSC spheres were also measured. The 3D sphere developed its osteogenic potency in a time-dependent manner, containing approximately 10-fold higher mineralization, 5-fold higher protein content, and 4-fold greater ALP activity than those in the controls. The expression of key osteogenic genes was also upregulated in the 3D PDLSC spheres. Cellular outgrowth was observed when reintroduced into 2D culture. PDLSCs were able to undergo osteogenic differentiation in a scaffold-free 3D culture, producing bonelike mineralization in vitro. This suggests, at least in vitro, the osteogenic potency of the 3D PDLSC spheres. Copyright © 2013 Elsevier Inc. All rights reserved.

GLO-Roots: An imaging platform enabling multidimensional characterization of soil-grown root systems

DOE PAGES

Rellan-Alvarez, Ruben; Lobet, Guillaume; Lindner, Heike; ...

2015-08-19

Root systems develop different root types that individually sense cues from their local environment and integrate this information with systemic signals. This complex multi-dimensional amalgam of inputs enables continuous adjustment of root growth rates, direction, and metabolic activity that define a dynamic physical network. Current methods for analyzing root biology balance physiological relevance with imaging capability. To bridge this divide, we developed an integrated-imaging system called Growth and Luminescence Observatory for Roots (GLO-Roots) that uses luminescence-based reporters to enable studies of root architecture and gene expression patterns in soil-grown, light-shielded roots. We have developed image analysis algorithms that allow themore » spatial integration of soil properties, gene expression, and root system architecture traits. We propose GLO-Roots as a system that has great utility in presenting environmental stimuli to roots in ways that evoke natural adaptive responses and in providing tools for studying the multi-dimensional nature of such processes.« less

Inference for High-dimensional Differential Correlation Matrices.

PubMed

Cai, T Tony; Zhang, Anru

2016-01-01

Motivated by differential co-expression analysis in genomics, we consider in this paper estimation and testing of high-dimensional differential correlation matrices. An adaptive thresholding procedure is introduced and theoretical guarantees are given. Minimax rate of convergence is established and the proposed estimator is shown to be adaptively rate-optimal over collections of paired correlation matrices with approximately sparse differences. Simulation results show that the procedure significantly outperforms two other natural methods that are based on separate estimation of the individual correlation matrices. The procedure is also illustrated through an analysis of a breast cancer dataset, which provides evidence at the gene co-expression level that several genes, of which a subset has been previously verified, are associated with the breast cancer. Hypothesis testing on the differential correlation matrices is also considered. A test, which is particularly well suited for testing against sparse alternatives, is introduced. In addition, other related problems, including estimation of a single sparse correlation matrix, estimation of the differential covariance matrices, and estimation of the differential cross-correlation matrices, are also discussed.

Two-dimensional gel analysis of protein expression in ovarian tumors shows a low degree of intratumoral heterogeneity.

PubMed

Alaiya, A A; Franzén, B; Moberger, B; Silfverswärd, C; Linder, S; Auer, G

1999-01-01

The process of tumor progression leads to the emergence of multiple clones, and to the development of tumor heterogeneity. One approach to the study of the extent of such heterogeneity is to examine the expression of marker proteins in different tumor areas. Two-dimensional gel electrophoresis (2-DE) is a powerful tool for such studies, since the expression of a large number of polypeptide markers can be evaluated. In the present study, tumor cells were prepared from human ovarian tumors and analyzed by 2-DE and PDQUEST. As judged from the analysis of two different areas in each of nine ovarian tumors, the intratumoral variation in protein expression was low. In contrast, large differences were observed when the protein profiles of different tumors were compared. The differences in gene expression between pairs of malignant carcinomas were slightly larger than the differences observed between pairs of benign tumors. We conclude that 2-DE analysis of intratumoral heterogeneity in ovarian cancer tissue indicates a low degree of heterogeneity.

DREISS: Using State-Space Models to Infer the Dynamics of Gene Expression Driven by External and Internal Regulatory Networks

PubMed Central

Gerstein, Mark

2016-01-01

Gene expression is controlled by the combinatorial effects of regulatory factors from different biological subsystems such as general transcription factors (TFs), cellular growth factors and microRNAs. A subsystem’s gene expression may be controlled by its internal regulatory factors, exclusively, or by external subsystems, or by both. It is thus useful to distinguish the degree to which a subsystem is regulated internally or externally–e.g., how non-conserved, species-specific TFs affect the expression of conserved, cross-species genes during evolution. We developed a computational method (DREISS, dreiss.gerteinlab.org) for analyzing the Dynamics of gene expression driven by Regulatory networks, both External and Internal based on State Space models. Given a subsystem, the “state” and “control” in the model refer to its own (internal) and another subsystem’s (external) gene expression levels. The state at a given time is determined by the state and control at a previous time. Because typical time-series data do not have enough samples to fully estimate the model’s parameters, DREISS uses dimensionality reduction, and identifies canonical temporal expression trajectories (e.g., degradation, growth and oscillation) representing the regulatory effects emanating from various subsystems. To demonstrate capabilities of DREISS, we study the regulatory effects of evolutionarily conserved vs. divergent TFs across distant species. In particular, we applied DREISS to the time-series gene expression datasets of C. elegans and D. melanogaster during their embryonic development. We analyzed the expression dynamics of the conserved, orthologous genes (orthologs), seeing the degree to which these can be accounted for by orthologous (internal) versus species-specific (external) TFs. We found that between two species, the orthologs have matched, internally driven expression patterns but very different externally driven ones. This is particularly true for genes with evolutionarily ancient functions (e.g. the ribosomal proteins), in contrast to those with more recently evolved functions (e.g., cell-cell communication). This suggests that despite striking morphological differences, some fundamental embryonic-developmental processes are still controlled by ancient regulatory systems. PMID:27760135

DREISS: Using State-Space Models to Infer the Dynamics of Gene Expression Driven by External and Internal Regulatory Networks.

PubMed

Wang, Daifeng; He, Fei; Maslov, Sergei; Gerstein, Mark

2016-10-01

Gene expression is controlled by the combinatorial effects of regulatory factors from different biological subsystems such as general transcription factors (TFs), cellular growth factors and microRNAs. A subsystem's gene expression may be controlled by its internal regulatory factors, exclusively, or by external subsystems, or by both. It is thus useful to distinguish the degree to which a subsystem is regulated internally or externally-e.g., how non-conserved, species-specific TFs affect the expression of conserved, cross-species genes during evolution. We developed a computational method (DREISS, dreiss.gerteinlab.org) for analyzing the Dynamics of gene expression driven by Regulatory networks, both External and Internal based on State Space models. Given a subsystem, the "state" and "control" in the model refer to its own (internal) and another subsystem's (external) gene expression levels. The state at a given time is determined by the state and control at a previous time. Because typical time-series data do not have enough samples to fully estimate the model's parameters, DREISS uses dimensionality reduction, and identifies canonical temporal expression trajectories (e.g., degradation, growth and oscillation) representing the regulatory effects emanating from various subsystems. To demonstrate capabilities of DREISS, we study the regulatory effects of evolutionarily conserved vs. divergent TFs across distant species. In particular, we applied DREISS to the time-series gene expression datasets of C. elegans and D. melanogaster during their embryonic development. We analyzed the expression dynamics of the conserved, orthologous genes (orthologs), seeing the degree to which these can be accounted for by orthologous (internal) versus species-specific (external) TFs. We found that between two species, the orthologs have matched, internally driven expression patterns but very different externally driven ones. This is particularly true for genes with evolutionarily ancient functions (e.g. the ribosomal proteins), in contrast to those with more recently evolved functions (e.g., cell-cell communication). This suggests that despite striking morphological differences, some fundamental embryonic-developmental processes are still controlled by ancient regulatory systems.

Sparse representation of multi parametric DCE-MRI features using K-SVD for classifying gene expression based breast cancer recurrence risk

NASA Astrophysics Data System (ADS)

Mahrooghy, Majid; Ashraf, Ahmed B.; Daye, Dania; Mies, Carolyn; Rosen, Mark; Feldman, Michael; Kontos, Despina

2014-03-01

We evaluate the prognostic value of sparse representation-based features by applying the K-SVD algorithm on multiparametric kinetic, textural, and morphologic features in breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). K-SVD is an iterative dimensionality reduction method that optimally reduces the initial feature space by updating the dictionary columns jointly with the sparse representation coefficients. Therefore, by using K-SVD, we not only provide sparse representation of the features and condense the information in a few coefficients but also we reduce the dimensionality. The extracted K-SVD features are evaluated by a machine learning algorithm including a logistic regression classifier for the task of classifying high versus low breast cancer recurrence risk as determined by a validated gene expression assay. The features are evaluated using ROC curve analysis and leave one-out cross validation for different sparse representation and dimensionality reduction numbers. Optimal sparse representation is obtained when the number of dictionary elements is 4 (K=4) and maximum non-zero coefficients is 2 (L=2). We compare K-SVD with ANOVA based feature selection for the same prognostic features. The ROC results show that the AUC of the K-SVD based (K=4, L=2), the ANOVA based, and the original features (i.e., no dimensionality reduction) are 0.78, 0.71. and 0.68, respectively. From the results, it can be inferred that by using sparse representation of the originally extracted multi-parametric, high-dimensional data, we can condense the information on a few coefficients with the highest predictive value. In addition, the dimensionality reduction introduced by K-SVD can prevent models from over-fitting.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fournier, Marcia V.; Martin, Katherine J.; Kenny, Paraic A.

To understand how non-malignant human mammary epithelial cells (HMEC) transit from a disorganized proliferating to an organized growth arrested state, and to relate this process to the changes that occur in breast cancer, we studied gene expression changes in non-malignant HMEC grown in three-dimensional cultures, and in a previously published panel of microarray data for 295 breast cancer samples. We hypothesized that the gene expression pattern of organized and growth arrested mammary acini would share similarities with breast tumors with good prognoses. Using Affymetrix HG-U133A microarrays, we analyzed the expression of 22,283 gene transcripts in two HMEC cell lines, 184more » (finite life span) and HMT3522 S1 (immortal non-malignant), on successive days post-seeding in a laminin-rich extracellular matrix assay. Both HMECs underwent growth arrest in G0/G1 and differentiated into polarized acini between days 5 and 7. We identified gene expression changes with the same temporal pattern in both lines. We show that genes that are significantly lower in the organized, growth arrested HMEC than in their proliferating counterparts can be used to classify breast cancer patients into poor and good prognosis groups with high accuracy. This study represents a novel unsupervised approach to identifying breast cancer markers that may be of use clinically.« less

Global Analysis of Differentially Expressed Genes and Proteins in the Wheat Callus Infected by Agrobacterium tumefaciens

PubMed Central

Zhou, Xiaohong; Wang, Ke; Lv, Dongwen; Wu, Chengjun; Li, Jiarui; Zhao, Pei; Lin, Zhishan; Du, Lipu; Yan, Yueming; Ye, Xingguo

2013-01-01

Agrobacterium-mediated plant transformation is an extremely complex and evolved process involving genetic determinants of both the bacteria and the host plant cells. However, the mechanism of the determinants remains obscure, especially in some cereal crops such as wheat, which is recalcitrant for Agrobacterium-mediated transformation. In this study, differentially expressed genes (DEGs) and differentially expressed proteins (DEPs) were analyzed in wheat callus cells co-cultured with Agrobacterium by using RNA sequencing (RNA-seq) and two-dimensional electrophoresis (2-DE) in conjunction with mass spectrometry (MS). A set of 4,889 DEGs and 90 DEPs were identified, respectively. Most of them are related to metabolism, chromatin assembly or disassembly and immune defense. After comparative analysis, 24 of the 90 DEPs were detected in RNA-seq and proteomics datasets simultaneously. In addition, real-time RT-PCR experiments were performed to check the differential expression of the 24 genes, and the results were consistent with the RNA-seq data. According to gene ontology (GO) analysis, we found that a big part of these differentially expressed genes were related to the process of stress or immunity response. Several putative determinants and candidate effectors responsive to Agrobacterium mediated transformation of wheat cells were discussed. We speculate that some of these genes are possibly related to Agrobacterium infection. Our results will help to understand the interaction between Agrobacterium and host cells, and may facilitate developing efficient transformation strategies in cereal crops. PMID:24278131

Distributed Function Mining for Gene Expression Programming Based on Fast Reduction.

PubMed

Deng, Song; Yue, Dong; Yang, Le-chan; Fu, Xiong; Feng, Ya-zhou

2016-01-01

For high-dimensional and massive data sets, traditional centralized gene expression programming (GEP) or improved algorithms lead to increased run-time and decreased prediction accuracy. To solve this problem, this paper proposes a new improved algorithm called distributed function mining for gene expression programming based on fast reduction (DFMGEP-FR). In DFMGEP-FR, fast attribution reduction in binary search algorithms (FAR-BSA) is proposed to quickly find the optimal attribution set, and the function consistency replacement algorithm is given to solve integration of the local function model. Thorough comparative experiments for DFMGEP-FR, centralized GEP and the parallel gene expression programming algorithm based on simulated annealing (parallel GEPSA) are included in this paper. For the waveform, mushroom, connect-4 and musk datasets, the comparative results show that the average time-consumption of DFMGEP-FR drops by 89.09%%, 88.85%, 85.79% and 93.06%, respectively, in contrast to centralized GEP and by 12.5%, 8.42%, 9.62% and 13.75%, respectively, compared with parallel GEPSA. Six well-studied UCI test data sets demonstrate the efficiency and capability of our proposed DFMGEP-FR algorithm for distributed function mining.

Cross-study projections of genomic biomarkers: an evaluation in cancer genomics.

PubMed

Lucas, Joseph E; Carvalho, Carlos M; Chen, Julia Ling-Yu; Chi, Jen-Tsan; West, Mike

2009-01-01

Human disease studies using DNA microarrays in both clinical/observational and experimental/controlled studies are having increasing impact on our understanding of the complexity of human diseases. A fundamental concept is the use of gene expression as a "common currency" that links the results of in vitro controlled experiments to in vivo observational human studies. Many studies--in cancer and other diseases--have shown promise in using in vitro cell manipulations to improve understanding of in vivo biology, but experiments often simply fail to reflect the enormous phenotypic variation seen in human diseases. We address this with a framework and methods to dissect, enhance and extend the in vivo utility of in vitro derived gene expression signatures. From an experimentally defined gene expression signature we use statistical factor analysis to generate multiple quantitative factors in human cancer gene expression data. These factors retain their relationship to the original, one-dimensional in vitro signature but better describe the diversity of in vivo biology. In a breast cancer analysis, we show that factors can reflect fundamentally different biological processes linked to molecular and clinical features of human cancers, and that in combination they can improve prediction of clinical outcomes.

A Primary Xenograft Model of Small Cell Lung Cancer Reveals Irreversible Changes in Gene Expression Imposed by Culture In-Vitro

PubMed Central

Daniel, Vincent C.; Marchionni, Luigi; Hierman, Jared S.; Rhodes, Jonathan T.; Devereux, Wendy L.; Rudin, Charles M.; Yung, Rex; Parmigani, Giovanni; Dorsch, Marion; Peacock, Craig D.; Watkins, D. Neil

2009-01-01

Traditional approaches to the preclinical investigation of cancer therapies rely on the use of established cell lines maintained in serum-based growth media. This is particularly true of small cell lung cancer (SCLC), where surgically resected tissue is rarely available. Recent attention has focused on the need for better models that preserve the integrity of cancer stem cell populations, as well as three-dimensional tumor-stromal interactions. Here we describe a primary xenograft model of SCLC in which endobronchial tumor specimens obtained from chemo-naive patients are serially propagated in vivo in immunodeficient mice. In parallel, cell lines grown in conventional tissue culture conditions were derived from each xenograft line, passaged for 6 months, and then re-implanted to generate secondary xenografts. Using the Affymetrix platform, we analyzed gene expression in primary xenograft, xenograft-derived cell line, and secondary xenograft, and compared these data to similar analyses of unrelated primary SCLC samples and laboratory models. When compared to normal lung, primary tumors, xenografts and cell lines displayed a gene expression signature specific for SCLC. Comparison of gene expression within the xenograft model identified a group of tumor-specific genes expressed in primary SCLC and xenografts that was lost during the transition to tissue culture, and that was not regained when the tumors were re-established as secondary xenografts. Such changes in gene expression may be a common feature of many cancer cell culture systems, with functional implications for the use of such models for preclinical drug development. PMID:19351829

Impact of Profiling Technologies in the Understanding of Recombinant Protein Production

NASA Astrophysics Data System (ADS)

Vijayendran, Chandran; Flaschel, Erwin

Since expression profiling methods have been available in a high throughput fashion, the implication of these technologies in the field of biotechnology has increased dramatically. Microarray technology is one such unique and efficient methodology for simultaneous exploration of expression levels of numerous genes. Likewise, two-dimensional gel electrophoresis or multidimensional liquid chromatography coupled with mass spectrometry are extensively utilised for studying expression levels of numerous proteins. In the field of biotechnology these highly parallel analytical methods have paved the way to study and understand various biological phenomena depending on expression patterns. The next phenomenological level is represented by the metabolome and the (metabolic) fluxome. However, this chapter reviews gene and protein profiling and their impact on understanding recombinant protein production. We focus on the computational methods utilised for the analyses of data obtained from these profiling technologies as well as prominent results focusing on recombinant protein expression with Escherichia coli. Owing to the knowledge accumulated with respect to cellular signals triggered during recombinant protein production, this field is on the way to design strategies for developing improved processes. Both gene and protein profiling have exhibited a handful of functional categories to concentrate on in order to identify target genes and proteins, respectively, involved in the signalling network with major impact on recombinant protein production.

Distributional fold change test – a statistical approach for detecting differential expression in microarray experiments

PubMed Central

2012-01-01

Background Because of the large volume of data and the intrinsic variation of data intensity observed in microarray experiments, different statistical methods have been used to systematically extract biological information and to quantify the associated uncertainty. The simplest method to identify differentially expressed genes is to evaluate the ratio of average intensities in two different conditions and consider all genes that differ by more than an arbitrary cut-off value to be differentially expressed. This filtering approach is not a statistical test and there is no associated value that can indicate the level of confidence in the designation of genes as differentially expressed or not differentially expressed. At the same time the fold change by itself provide valuable information and it is important to find unambiguous ways of using this information in expression data treatment. Results A new method of finding differentially expressed genes, called distributional fold change (DFC) test is introduced. The method is based on an analysis of the intensity distribution of all microarray probe sets mapped to a three dimensional feature space composed of average expression level, average difference of gene expression and total variance. The proposed method allows one to rank each feature based on the signal-to-noise ratio and to ascertain for each feature the confidence level and power for being differentially expressed. The performance of the new method was evaluated using the total and partial area under receiver operating curves and tested on 11 data sets from Gene Omnibus Database with independently verified differentially expressed genes and compared with the t-test and shrinkage t-test. Overall the DFC test performed the best – on average it had higher sensitivity and partial AUC and its elevation was most prominent in the low range of differentially expressed features, typical for formalin-fixed paraffin-embedded sample sets. Conclusions The distributional fold change test is an effective method for finding and ranking differentially expressed probesets on microarrays. The application of this test is advantageous to data sets using formalin-fixed paraffin-embedded samples or other systems where degradation effects diminish the applicability of correlation adjusted methods to the whole feature set. PMID:23122055

Gluten affects epithelial differentiation-associated genes in small intestinal mucosa of coeliac patients

PubMed Central

Juuti-Uusitalo, K; Mäki, M; Kainulainen, H; Isola, J; Kaukinen, K

2007-01-01

In coeliac disease gluten induces an immunological reaction in genetically susceptible patients, and influences on epithelial cell proliferation and differentiation in the small-bowel mucosa. Our aim was to find novel genes which operate similarly in epithelial proliferation and differentiation in an epithelial cell differentiation model and in coeliac disease patient small-bowel mucosal biopsy samples. The combination of cDNA microarray data originating from a three-dimensional T84 epithelial cell differentiation model and small-bowel mucosal biopsy samples from untreated and treated coeliac disease patients and healthy controls resulted in 30 genes whose mRNA expression was similarly affected. Nine of 30 were located directly or indirectly in the receptor tyrosine kinase pathway starting from the epithelial growth factor receptor. Removal of gluten from the diet resulted in a reversion in the expression of 29 of the 30 genes in the small-bowel mucosal biopsy samples. Further characterization by blotting and labelling revealed increased epidermal growth factor receptor and beta-catenin protein expression in the small-bowel mucosal epithelium in untreated coeliac disease patients compared to healthy controls and treated coeliac patients. We found 30 genes whose mRNA expression was affected similarly in the epithelial cell differentiation model and in the coeliac disease patient small-bowel mucosal biopsy samples. In particular, those genes involved in the epithelial growth factor-mediated signalling pathways may be involved in epithelial cell differentiation and coeliac disease pathogenesis. The epithelial cell differentiation model is a useful tool for studying gene expression changes in the crypt–villus axis. PMID:17888028

An open reading frame in intron seven of the sea urchin DNA-methyltransferase gene codes for a functional AP1 endonuclease.

PubMed

Cioffi, Anna Valentina; Ferrara, Diana; Cubellis, Maria Vittoria; Aniello, Francesco; Corrado, Marcella; Liguori, Francesca; Amoroso, Alessandro; Fucci, Laura; Branno, Margherita

2002-08-01

Analysis of the genome structure of the Paracentrotus lividus (sea urchin) DNA methyltransferase (DNA MTase) gene showed the presence of an open reading frame, named METEX, in intron 7 of the gene. METEX expression is developmentally regulated, showing no correlation with DNA MTase expression. In fact, DNA MTase transcripts are present at high concentrations in the early developmental stages, while METEX is expressed at late stages of development. Two METEX cDNA clones (Met1 and Met2) that are different in the 3' end have been isolated in a cDNA library screening. The putative translated protein from Met2 cDNA clone showed similarity with Escherichia coli endonuclease III on the basis of sequence and predictive three-dimensional structure. The protein, overexpressed in E. coli and purified, had functional properties similar to the endonuclease specific for apurinic/apyrimidinic (AP) sites on the basis of the lyase activity. Therefore the open reading frame, present in intron 7 of the P. lividus DNA MTase gene, codes for a functional AP endonuclease designated SuAP1.

Cancer, Warts, or Asymptomatic Infections: Clinical Presentation Matches Codon Usage Preferences in Human Papillomaviruses

PubMed Central

Félez-Sánchez, Marta; Trösemeier, Jan-Hendrik; Bedhomme, Stéphanie; González-Bravo, Maria Isabel; Kamp, Christel; Bravo, Ignacio G.

2015-01-01

Viruses rely completely on the hosts’ machinery for translation of viral transcripts. However, for most viruses infecting humans, codon usage preferences (CUPrefs) do not match those of the host. Human papillomaviruses (HPVs) are a showcase to tackle this paradox: they present a large genotypic diversity and a broad range of phenotypic presentations, from asymptomatic infections to productive lesions and cancer. By applying phylogenetic inference and dimensionality reduction methods, we demonstrate first that genes in HPVs are poorly adapted to the average human CUPrefs, the only exception being capsid genes in viruses causing productive lesions. Phylogenetic relationships between HPVs explained only a small proportion of CUPrefs variation. Instead, the most important explanatory factor for viral CUPrefs was infection phenotype, as orthologous genes in viruses with similar clinical presentation displayed similar CUPrefs. Moreover, viral genes with similar spatiotemporal expression patterns also showed similar CUPrefs. Our results suggest that CUPrefs in HPVs reflect either variations in the mutation bias or differential selection pressures depending on the clinical presentation and expression timing. We propose that poor viral CUPrefs may be central to a trade-off between strong viral gene expression and the potential for eliciting protective immune response. PMID:26139833

Multifunctionality and diversity of GDSL esterase/lipase gene family in rice (Oryza sativa L. japonica) genome: new insights from bioinformatics analysis

PubMed Central

2012-01-01

Background GDSL esterases/lipases are a newly discovered subclass of lipolytic enzymes that are very important and attractive research subjects because of their multifunctional properties, such as broad substrate specificity and regiospecificity. Compared with the current knowledge regarding these enzymes in bacteria, our understanding of the plant GDSL enzymes is very limited, although the GDSL gene family in plant species include numerous members in many fully sequenced plant genomes. Only two genes from a large rice GDSL esterase/lipase gene family were previously characterised, and the majority of the members remain unknown. In the present study, we describe the rice OsGELP (Oryza sativa GDSL esterase/lipase protein) gene family at the genomic and proteomic levels, and use this knowledge to provide insights into the multifunctionality of the rice OsGELP enzymes. Results In this study, an extensive bioinformatics analysis identified 114 genes in the rice OsGELP gene family. A complete overview of this family in rice is presented, including the chromosome locations, gene structures, phylogeny, and protein motifs. Among the OsGELPs and the plant GDSL esterase/lipase proteins of known functions, 41 motifs were found that represent the core secondary structure elements or appear specifically in different phylogenetic subclades. The specification and distribution of identified putative conserved clade-common and -specific peptide motifs, and their location on the predicted protein three dimensional structure may possibly signify their functional roles. Potentially important regions for substrate specificity are highlighted, in accordance with protein three-dimensional model and location of the phylogenetic specific conserved motifs. The differential expression of some representative genes were confirmed by quantitative real-time PCR. The phylogenetic analysis, together with protein motif architectures, and the expression profiling were analysed to predict the possible biological functions of the rice OsGELP genes. Conclusions Our current genomic analysis, for the first time, presents fundamental information on the organization of the rice OsGELP gene family. With combination of the genomic, phylogenetic, microarray expression, protein motif distribution, and protein structure analyses, we were able to create supported basis for the functional prediction of many members in the rice GDSL esterase/lipase family. The present study provides a platform for the selection of candidate genes for further detailed functional study. PMID:22793791

Gene selection with multiple ordering criteria.

PubMed

Chen, James J; Tsai, Chen-An; Tzeng, Shengli; Chen, Chun-Houh

2007-03-05

A microarray study may select different differentially expressed gene sets because of different selection criteria. For example, the fold-change and p-value are two commonly known criteria to select differentially expressed genes under two experimental conditions. These two selection criteria often result in incompatible selected gene sets. Also, in a two-factor, say, treatment by time experiment, the investigator may be interested in one gene list that responds to both treatment and time effects. We propose three layer ranking algorithms, point-admissible, line-admissible (convex), and Pareto, to provide a preference gene list from multiple gene lists generated by different ranking criteria. Using the public colon data as an example, the layer ranking algorithms are applied to the three univariate ranking criteria, fold-change, p-value, and frequency of selections by the SVM-RFE classifier. A simulation experiment shows that for experiments with small or moderate sample sizes (less than 20 per group) and detecting a 4-fold change or less, the two-dimensional (p-value and fold-change) convex layer ranking selects differentially expressed genes with generally lower FDR and higher power than the standard p-value ranking. Three applications are presented. The first application illustrates a use of the layer rankings to potentially improve predictive accuracy. The second application illustrates an application to a two-factor experiment involving two dose levels and two time points. The layer rankings are applied to selecting differentially expressed genes relating to the dose and time effects. In the third application, the layer rankings are applied to a benchmark data set consisting of three dilution concentrations to provide a ranking system from a long list of differentially expressed genes generated from the three dilution concentrations. The layer ranking algorithms are useful to help investigators in selecting the most promising genes from multiple gene lists generated by different filter, normalization, or analysis methods for various objectives.

Finding differentially expressed genes in high dimensional data: Rank based test statistic via a distance measure.

PubMed

Mathur, Sunil; Sadana, Ajit

2015-12-01

We present a rank-based test statistic for the identification of differentially expressed genes using a distance measure. The proposed test statistic is highly robust against extreme values and does not assume the distribution of parent population. Simulation studies show that the proposed test is more powerful than some of the commonly used methods, such as paired t-test, Wilcoxon signed rank test, and significance analysis of microarray (SAM) under certain non-normal distributions. The asymptotic distribution of the test statistic, and the p-value function are discussed. The application of proposed method is shown using a real-life data set. © The Author(s) 2011.

Dynamic changes in the interchromosomal interaction of early histone gene loci during development of sea urchin.

PubMed

Matsushita, Masaya; Ochiai, Hiroshi; Suzuki, Ken-Ichi T; Hayashi, Sayaka; Yamamoto, Takashi; Awazu, Akinori; Sakamoto, Naoaki

2017-12-15

The nuclear positioning and chromatin dynamics of eukaryotic genes are closely related to the regulation of gene expression, but they have not been well examined during early development, which is accompanied by rapid cell cycle progression and dynamic changes in nuclear organization, such as nuclear size and chromatin constitution. In this study, we focused on the early development of the sea urchin Hemicentrotus pulcherrimus and performed three-dimensional fluorescence in situ hybridization of gene loci encoding early histones (one of the types of histone in sea urchin). There are two non-allelic early histone gene loci per sea urchin genome. We found that during the morula stage, when the early histone gene expression levels are at their maximum, interchromosomal interactions were often formed between the early histone gene loci on separate chromosomes and that the gene loci were directed to locate to more interior positions. Furthermore, these interactions were associated with the active transcription of the early histone genes. Thus, such dynamic interchromosomal interactions may contribute to the efficient synthesis of early histone mRNA during the morula stage of sea urchin development. © 2017. Published by The Company of Biologists Ltd.

The innate immune response in fetal lung mesenchymal cells targets VEGFR2 expression and activity.

PubMed

Medal, Rachel M; Im, Amanda M; Yamamoto, Yasutoshi; Lakhdari, Omar; Blackwell, Timothy S; Hoffman, Hal M; Sahoo, Debashis; Prince, Lawrence S

2017-06-01

In preterm infants, soluble inflammatory mediators target lung mesenchymal cells, disrupting airway and alveolar morphogenesis. However, how mesenchymal cells respond directly to microbial stimuli remains poorly characterized. Our objective was to measure the genome-wide innate immune response in fetal lung mesenchymal cells exposed to the bacterial endotoxin lipopolysaccharide (LPS). With the use of Affymetrix MoGene 1.0st arrays, we showed that LPS induced expression of unique innate immune transcripts heavily weighted toward CC and CXC family chemokines. The transcriptional response was different between cells from E11, E15, and E18 mouse lungs. In all cells tested, LPS inhibited expression of a small core group of genes including the VEGF receptor Vegfr2 Although best characterized in vascular endothelial populations, we demonstrated here that fetal mouse lung mesenchymal cells express Vegfr2 and respond to VEGF-A stimulation. In mesenchymal cells, VEGF-A increased cell migration, activated the ERK/AKT pathway, and promoted FOXO3A nuclear exclusion. With the use of an experimental coculture model of epithelial-mesenchymal interactions, we also showed that VEGFR2 inhibition prevented formation of three-dimensional structures. Both LPS and tyrosine kinase inhibition reduced three-dimensional structure formation. Our data suggest a novel mechanism for inflammation-mediated defects in lung development involving reduced VEGF signaling in lung mesenchyme. Copyright © 2017 the American Physiological Society.

Functional Analysis of Developmentally Regulated Genes chs7 and sec22 in the Ascomycete Sordaria macrospora.

PubMed

Traeger, Stefanie; Nowrousian, Minou

2015-04-14

During sexual development, filamentous ascomycetes form complex, three-dimensional fruiting bodies for the generation and dispersal of spores. In previous studies, we identified genes with evolutionary conserved expression patterns during fruiting body formation in several fungal species. Here, we present the functional analysis of two developmentally up-regulated genes, chs7 and sec22, in the ascomycete Sordaria macrospora. The genes encode a class VII (division III) chitin synthase and a soluble N-ethylmaleimide-sensitive-factor attachment protein receptor (SNARE) protein, respectively. Deletion mutants of chs7 had normal vegetative growth and were fully fertile but showed sensitivity toward cell wall stress. Deletion of sec22 resulted in a reduced number of ascospores and in defects in ascospore pigmentation and germination, whereas vegetative growth was normal in the mutant. A SEC22-EGFP fusion construct under control of the native sec22 promoter and terminator regions was expressed during different stages of sexual development. Expression of several development-related genes was deregulated in the sec22 mutant, including three genes involved in melanin biosynthesis. Our data indicate that chs7 is dispensable for fruiting body formation in S. macrospora, whereas sec22 is required for ascospore maturation and germination and thus involved in late stages of sexual development. Copyright © 2015 Traeger and Nowrousian.

Functional Analysis of Developmentally Regulated Genes chs7 and sec22 in the Ascomycete Sordaria macrospora

PubMed Central

Traeger, Stefanie; Nowrousian, Minou

2015-01-01

During sexual development, filamentous ascomycetes form complex, three-dimensional fruiting bodies for the generation and dispersal of spores. In previous studies, we identified genes with evolutionary conserved expression patterns during fruiting body formation in several fungal species. Here, we present the functional analysis of two developmentally up-regulated genes, chs7 and sec22, in the ascomycete Sordaria macrospora. The genes encode a class VII (division III) chitin synthase and a soluble N-ethylmaleimide-sensitive-factor attachment protein receptor (SNARE) protein, respectively. Deletion mutants of chs7 had normal vegetative growth and were fully fertile but showed sensitivity toward cell wall stress. Deletion of sec22 resulted in a reduced number of ascospores and in defects in ascospore pigmentation and germination, whereas vegetative growth was normal in the mutant. A SEC22-EGFP fusion construct under control of the native sec22 promoter and terminator regions was expressed during different stages of sexual development. Expression of several development-related genes was deregulated in the sec22 mutant, including three genes involved in melanin biosynthesis. Our data indicate that chs7 is dispensable for fruiting body formation in S. macrospora, whereas sec22 is required for ascospore maturation and germination and thus involved in late stages of sexual development. PMID:25873638

Morphogenesis in Plants: Modeling the Shoot Apical Meristem, and Possible Applications

NASA Technical Reports Server (NTRS)

Mjolsness, Eric; Gor, Victoria; Meyerowitz, Elliot; Mann, Tobias

1998-01-01

A key determinant of overall morphogenesis in flowering plants such as Arabidopsis thaliana is the shoot apical meristem (growing tip of a shoot). Gene regulation networks can be used to model this system. We exhibit a very preliminary two-dimensional model including gene regulation and intercellular signaling, but omitting cell division and dynamical geometry. The model can be trained to have three stable regions of gene expression corresponding to the central zone, peripheral zone, and rib meristem. We also discuss a space-engineering motivation for studying and controlling the morphogenesis of plants using such computational models.

High-dimensional gene expression profiling studies in high and low responders to primary smallpox vaccination.

PubMed

Haralambieva, Iana H; Oberg, Ann L; Dhiman, Neelam; Ovsyannikova, Inna G; Kennedy, Richard B; Grill, Diane E; Jacobson, Robert M; Poland, Gregory A

2012-11-15

The mechanisms underlying smallpox vaccine-induced variations in immune responses are not well understood, but are of considerable interest to a deeper understanding of poxvirus immunity and correlates of protection. We assessed transcriptional messenger RNA expression changes in 197 recipients of primary smallpox vaccination representing the extremes of humoral and cellular immune responses. The 20 most significant differentially expressed genes include a tumor necrosis factor-receptor superfamily member, an interferon (IFN) gene, a chemokine gene, zinc finger protein genes, nuclear factors, and histones (P ≤ 1.06E(-20), q ≤ 2.64E(-17)). A pathway analysis identified 4 enriched pathways with cytokine production by the T-helper 17 subset of CD4+ T cells being the most significant pathway (P = 3.42E(-05)). Two pathways (antiviral actions of IFNs, P = 8.95E(-05); and IFN-α/β signaling pathway, P = 2.92E(-04)), integral to innate immunity, were enriched when comparing high with low antibody responders (false discovery rate, < 0.05). Genes related to immune function and transcription (TLR8, P = .0002; DAPP1, P = .0003; LAMP3, P = 9.96E(-05); NR4A2, P ≤ .0002; EGR3, P = 4.52E(-05)), and other genes with a possible impact on immunity (LNPEP, P = 3.72E(-05); CAPRIN1, P = .0001; XRN1, P = .0001), were found to be expressed differentially in high versus low antibody responders. We identified novel and known immunity-related genes and pathways that may account for differences in immune response to smallpox vaccination.

A Novel Hybrid Dimension Reduction Technique for Undersized High Dimensional Gene Expression Data Sets Using Information Complexity Criterion for Cancer Classification

PubMed Central

Pamukçu, Esra; Bozdogan, Hamparsum; Çalık, Sinan

2015-01-01

Gene expression data typically are large, complex, and highly noisy. Their dimension is high with several thousand genes (i.e., features) but with only a limited number of observations (i.e., samples). Although the classical principal component analysis (PCA) method is widely used as a first standard step in dimension reduction and in supervised and unsupervised classification, it suffers from several shortcomings in the case of data sets involving undersized samples, since the sample covariance matrix degenerates and becomes singular. In this paper we address these limitations within the context of probabilistic PCA (PPCA) by introducing and developing a new and novel approach using maximum entropy covariance matrix and its hybridized smoothed covariance estimators. To reduce the dimensionality of the data and to choose the number of probabilistic PCs (PPCs) to be retained, we further introduce and develop celebrated Akaike's information criterion (AIC), consistent Akaike's information criterion (CAIC), and the information theoretic measure of complexity (ICOMP) criterion of Bozdogan. Six publicly available undersized benchmark data sets were analyzed to show the utility, flexibility, and versatility of our approach with hybridized smoothed covariance matrix estimators, which do not degenerate to perform the PPCA to reduce the dimension and to carry out supervised classification of cancer groups in high dimensions. PMID:25838836

Higher order genomic organization and regulatory compartmentalization for cell cycle control at the G1/S-phase transition.

PubMed

Ghule, Prachi N; Seward, David J; Fritz, Andrew J; Boyd, Joseph R; van Wijnen, Andre J; Lian, Jane B; Stein, Janet L; Stein, Gary S

2018-05-10

Fidelity of histone gene regulation, and ultimately of histone protein biosynthesis, is obligatory for packaging of newly replicated DNA into chromatin. Control of histone gene expression within the 3-dimensional context of nuclear organization is reflected by two well documented observations. DNA replication-dependent histone mRNAs are synthesized at specialized subnuclear domains designated histone locus bodies (HLBs), in response to activation of the growth factor dependent Cyclin E/CDK2/HINFP/NPAT pathway at the G1/S transition in mammalian cells. Complete loss of the histone gene regulatory factors HINFP or NPAT disrupts HLB integrity that is necessary for coordinate control of DNA replication and histone gene transcription. Here we review the molecular histone-related requirements for G1/S-phase progression during the cell cycle. Recently developed experimental strategies, now enable us to explore mechanisms involved in dynamic control of histone gene expression in the context of the temporal (cell cycle) and spatial (HLBs) remodeling of the histone gene loci. © 2018 Wiley Periodicals, Inc.

High-Dimensional Heteroscedastic Regression with an Application to eQTL Data Analysis

PubMed Central

Daye, Z. John; Chen, Jinbo; Li, Hongzhe

2011-01-01

Summary We consider the problem of high-dimensional regression under non-constant error variances. Despite being a common phenomenon in biological applications, heteroscedasticity has, so far, been largely ignored in high-dimensional analysis of genomic data sets. We propose a new methodology that allows non-constant error variances for high-dimensional estimation and model selection. Our method incorporates heteroscedasticity by simultaneously modeling both the mean and variance components via a novel doubly regularized approach. Extensive Monte Carlo simulations indicate that our proposed procedure can result in better estimation and variable selection than existing methods when heteroscedasticity arises from the presence of predictors explaining error variances and outliers. Further, we demonstrate the presence of heteroscedasticity in and apply our method to an expression quantitative trait loci (eQTLs) study of 112 yeast segregants. The new procedure can automatically account for heteroscedasticity in identifying the eQTLs that are associated with gene expression variations and lead to smaller prediction errors. These results demonstrate the importance of considering heteroscedasticity in eQTL data analysis. PMID:22547833

From SHAPE Signatures to 3-D Structures | Center for Cancer Research

Cancer.gov

RNAs undergo extensive folding to form sophisticated based-paired secondary structures that are, in part, indicators of more complex three-dimensional structures.  These 3-D shapes are an integral part of the cellular gene-expression machinery. Deconstructing these structures is no small matter, yet it is critical to understanding their function.

Inference for High-dimensional Differential Correlation Matrices *

PubMed Central

Cai, T. Tony; Zhang, Anru

2015-01-01

Motivated by differential co-expression analysis in genomics, we consider in this paper estimation and testing of high-dimensional differential correlation matrices. An adaptive thresholding procedure is introduced and theoretical guarantees are given. Minimax rate of convergence is established and the proposed estimator is shown to be adaptively rate-optimal over collections of paired correlation matrices with approximately sparse differences. Simulation results show that the procedure significantly outperforms two other natural methods that are based on separate estimation of the individual correlation matrices. The procedure is also illustrated through an analysis of a breast cancer dataset, which provides evidence at the gene co-expression level that several genes, of which a subset has been previously verified, are associated with the breast cancer. Hypothesis testing on the differential correlation matrices is also considered. A test, which is particularly well suited for testing against sparse alternatives, is introduced. In addition, other related problems, including estimation of a single sparse correlation matrix, estimation of the differential covariance matrices, and estimation of the differential cross-correlation matrices, are also discussed. PMID:26500380

BATS: a Bayesian user-friendly software for analyzing time series microarray experiments.

PubMed

Angelini, Claudia; Cutillo, Luisa; De Canditiis, Daniela; Mutarelli, Margherita; Pensky, Marianna

2008-10-06

Gene expression levels in a given cell can be influenced by different factors, namely pharmacological or medical treatments. The response to a given stimulus is usually different for different genes and may depend on time. One of the goals of modern molecular biology is the high-throughput identification of genes associated with a particular treatment or a biological process of interest. From methodological and computational point of view, analyzing high-dimensional time course microarray data requires very specific set of tools which are usually not included in standard software packages. Recently, the authors of this paper developed a fully Bayesian approach which allows one to identify differentially expressed genes in a 'one-sample' time-course microarray experiment, to rank them and to estimate their expression profiles. The method is based on explicit expressions for calculations and, hence, very computationally efficient. The software package BATS (Bayesian Analysis of Time Series) presented here implements the methodology described above. It allows an user to automatically identify and rank differentially expressed genes and to estimate their expression profiles when at least 5-6 time points are available. The package has a user-friendly interface. BATS successfully manages various technical difficulties which arise in time-course microarray experiments, such as a small number of observations, non-uniform sampling intervals and replicated or missing data. BATS is a free user-friendly software for the analysis of both simulated and real microarray time course experiments. The software, the user manual and a brief illustrative example are freely available online at the BATS website: http://www.na.iac.cnr.it/bats.

Associations of chemo- and radio-resistant phenotypes with the gap junction, adhesion and extracellular matrix in a three-dimensional culture model of soft sarcoma.

PubMed

Bai, Chujie; Yang, Min; Fan, Zhengfu; Li, Shu; Gao, Tian; Fang, Zhiwei

2015-06-10

Three-dimensional (3D) culture models are considered to recapitulate the cell microenvironment in solid tumors, including the extracellular matrix (ECM), cell-cell interactions, and signal transduction. These functions are highly correlated with cellular behaviors and contribute to resistances against chemo- and radio-therapies. However, the biochemical effects and mechanisms remain unknown in soft sarcoma. Therefore, we developed an in vitro 3D model of sarcoma to analyze the reasons of the chemo- and radio-resistance in therapies. Four soft sarcoma cell lines, HT1080, RD, SW872, and human osteosarcoma cell line 1 (HOSS1), a cell line established from a patient-derived xenograft, were applied to 3D culture and treated with growth factors in methylcellulose-containing medium. Spheroids were examined morphologically and by western blotting, RT-qPCR, and immunofluorescence staining to analyze cell adhesion, gap junctions, ECM genes, and related factors. Proliferation and colony formation assays were performed to assess chemo- and radio-resistances between 3D and two-dimensional (2D) cell cultures. Annexin V and Propidium Iodide staining was used to detect early apoptotic sarcoma cells treated with Doxorubicin, Gemcitabine, and Docetaxel in the 3D model. The four soft sarcoma cell lines formed spheres in vitro by culture in modified condition medium. Compared with 2D cell culture, expression of ECM genes and proteins, including COL1A1, LOX, SED1, FN1, and LAMA4, was significantly increased in 3D culture. Analysis of cadherin and gap junction molecules showed significant changes in the gene and protein expression profiles under 3D conditions. These changes affected cell-cell communication and were mainly associated with biological processes such as cell proliferation and apoptosis related to chemo- and radio-resistances. Our findings revealed significant differences between 3D and 2D cell culture systems, and indicated that cellular responsiveness to external stress such as radiation and chemotherapeutics is influenced by differential expression of genes and proteins involved in regulation of the ECM, cell adhesion, and gap junction signaling.

Comprehensive single cell-resolution analysis of the role of chromatin regulators in early C. elegans embryogenesis.

PubMed

Krüger, Angela V; Jelier, Rob; Dzyubachyk, Oleh; Zimmerman, Timo; Meijering, Erik; Lehner, Ben

2015-02-15

Chromatin regulators are widely expressed proteins with diverse roles in gene expression, nuclear organization, cell cycle regulation, pluripotency, physiology and development, and are frequently mutated in human diseases such as cancer. Their inhibition often results in pleiotropic effects that are difficult to study using conventional approaches. We have developed a semi-automated nuclear tracking algorithm to quantify the divisions, movements and positions of all nuclei during the early development of Caenorhabditis elegans and have used it to systematically study the effects of inhibiting chromatin regulators. The resulting high dimensional datasets revealed that inhibition of multiple regulators, including F55A3.3 (encoding FACT subunit SUPT16H), lin-53 (RBBP4/7), rba-1 (RBBP4/7), set-16 (MLL2/3), hda-1 (HDAC1/2), swsn-7 (ARID2), and let-526 (ARID1A/1B) affected cell cycle progression and caused chromosome segregation defects. In contrast, inhibition of cir-1 (CIR1) accelerated cell division timing in specific cells of the AB lineage. The inhibition of RNA polymerase II also accelerated these division timings, suggesting that normal gene expression is required to delay cell cycle progression in multiple lineages in the early embryo. Quantitative analyses of the dataset suggested the existence of at least two functionally distinct SWI/SNF chromatin remodeling complex activities in the early embryo, and identified a redundant requirement for the egl-27 and lin-40 MTA orthologs in the development of endoderm and mesoderm lineages. Moreover, our dataset also revealed a characteristic rearrangement of chromatin to the nuclear periphery upon the inhibition of multiple general regulators of gene expression. Our systematic, comprehensive and quantitative datasets illustrate the power of single cell-resolution quantitative tracking and high dimensional phenotyping to investigate gene function. Furthermore, the results provide an overview of the functions of essential chromatin regulators during the early development of an animal. Copyright © 2014 Elsevier Inc. All rights reserved.

Condensin-driven remodelling of X chromosome topology during dosage compensation

NASA Astrophysics Data System (ADS)

Crane, Emily; Bian, Qian; McCord, Rachel Patton; Lajoie, Bryan R.; Wheeler, Bayly S.; Ralston, Edward J.; Uzawa, Satoru; Dekker, Job; Meyer, Barbara J.

2015-07-01

The three-dimensional organization of a genome plays a critical role in regulating gene expression, yet little is known about the machinery and mechanisms that determine higher-order chromosome structure. Here we perform genome-wide chromosome conformation capture analysis, fluorescent in situ hybridization (FISH), and RNA-seq to obtain comprehensive three-dimensional (3D) maps of the Caenorhabditis elegans genome and to dissect X chromosome dosage compensation, which balances gene expression between XX hermaphrodites and XO males. The dosage compensation complex (DCC), a condensin complex, binds to both hermaphrodite X chromosomes via sequence-specific recruitment elements on X (rex sites) to reduce chromosome-wide gene expression by half. Most DCC condensin subunits also act in other condensin complexes to control the compaction and resolution of all mitotic and meiotic chromosomes. By comparing chromosome structure in wild-type and DCC-defective embryos, we show that the DCC remodels hermaphrodite X chromosomes into a sex-specific spatial conformation distinct from autosomes. Dosage-compensated X chromosomes consist of self-interacting domains (~1 Mb) resembling mammalian topologically associating domains (TADs). TADs on X chromosomes have stronger boundaries and more regular spacing than on autosomes. Many TAD boundaries on X chromosomes coincide with the highest-affinity rex sites and become diminished or lost in DCC-defective mutants, thereby converting the topology of X to a conformation resembling autosomes. rex sites engage in DCC-dependent long-range interactions, with the most frequent interactions occurring between rex sites at DCC-dependent TAD boundaries. These results imply that the DCC reshapes the topology of X chromosomes by forming new TAD boundaries and reinforcing weak boundaries through interactions between its highest-affinity binding sites. As this model predicts, deletion of an endogenous rex site at a DCC-dependent TAD boundary using CRISPR/Cas9 greatly diminished the boundary. Thus, the DCC imposes a distinct higher-order structure onto X chromosomes while regulating gene expression chromosome-wide.

Methodological study of affine transformations of gene expression data with proposed robust non-parametric multi-dimensional normalization method.

PubMed

Bengtsson, Henrik; Hössjer, Ola

2006-03-01

Low-level processing and normalization of microarray data are most important steps in microarray analysis, which have profound impact on downstream analysis. Multiple methods have been suggested to date, but it is not clear which is the best. It is therefore important to further study the different normalization methods in detail and the nature of microarray data in general. A methodological study of affine models for gene expression data is carried out. Focus is on two-channel comparative studies, but the findings generalize also to single- and multi-channel data. The discussion applies to spotted as well as in-situ synthesized microarray data. Existing normalization methods such as curve-fit ("lowess") normalization, parallel and perpendicular translation normalization, and quantile normalization, but also dye-swap normalization are revisited in the light of the affine model and their strengths and weaknesses are investigated in this context. As a direct result from this study, we propose a robust non-parametric multi-dimensional affine normalization method, which can be applied to any number of microarrays with any number of channels either individually or all at once. A high-quality cDNA microarray data set with spike-in controls is used to demonstrate the power of the affine model and the proposed normalization method. We find that an affine model can explain non-linear intensity-dependent systematic effects in observed log-ratios. Affine normalization removes such artifacts for non-differentially expressed genes and assures that symmetry between negative and positive log-ratios is obtained, which is fundamental when identifying differentially expressed genes. In addition, affine normalization makes the empirical distributions in different channels more equal, which is the purpose of quantile normalization, and may also explain why dye-swap normalization works or fails. All methods are made available in the aroma package, which is a platform-independent package for R.

IGF-1 promotes angiogenesis in endothelial cells/adipose-derived stem cells co-culture system with activation of PI3K/Akt signal pathway.

PubMed

Lin, Shiyu; Zhang, Qi; Shao, Xiaoru; Zhang, Tao; Xue, Changyue; Shi, Sirong; Zhao, Dan; Lin, Yunfeng

2017-12-01

The aim of this study was to investigate the role of insulin-like growth factor-1 (IGF-1) and crosstalk between endothelial cells (ECs) and adipose-derived stem cells (ASCs) in the process of angiogenesis. A three-dimensional collagen gel used to culture mouse ASCs and mouse ECs in vitro was established. The effects of angiogenesis after exposure to IGF-1 were observed by confocal laser scanning microscopy. Western blotting and qPCR were performed to elucidate the underlying mechanisms. IGF-1 treatment promoted the formation of vessel-like structures and the recruitment of ASCs in the three-dimensional collagen gel. The angiogenic genes and proteins in ECs were up-regulated by IGF-1 and in co-culture. Similar changes in the genes and in the proteins were detected in ASCs after exposure to IGF-1 and co-culture. p-Akt expression levels were high in ECs and ASCs after exposure to IGF-1 and co-culture. IGF-1 and co-culture between cells facilitate the process of angiogenesis via the PI3-kinase/Akt signalling pathway. In ECs, IGF-1 stimulates the expression of angiogenesis-related growth factors with the activation of the PI3-kinase/Akt signalling pathway. Co-cultured ECs exposed to excess VEGF-A and other angiogenesis-related growth factors para-secreted from ASCs exhibit high expression of angiogenesis-related genes and proteins. In ASCs, IGF-1 induces the recruitment and function of ASCs by up-regulating the expression of PDGFB, MMPs and α-SMA. Crosstalk with ECs further facilitates changes in ASCs. © 2017 John Wiley & Sons Ltd.

GAC: Gene Associations with Clinical, a web based application.

PubMed

Zhang, Xinyan; Rupji, Manali; Kowalski, Jeanne

2017-01-01

We present GAC, a shiny R based tool for interactive visualization of clinical associations based on high-dimensional data. The tool provides a web-based suite to perform supervised principal component analysis (SuperPC), an approach that uses both high-dimensional data, such as gene expression, combined with clinical data to infer clinical associations. We extended the approach to address binary outcomes, in addition to continuous and time-to-event data in our package, thereby increasing the use and flexibility of SuperPC.  Additionally, the tool provides an interactive visualization for summarizing results based on a forest plot for both binary and time-to-event data.  In summary, the GAC suite of tools provide a one stop shop for conducting statistical analysis to identify and visualize the association between a clinical outcome of interest and high-dimensional data types, such as genomic data. Our GAC package has been implemented in R and is available via http://shinygispa.winship.emory.edu/GAC/. The developmental repository is available at https://github.com/manalirupji/GAC.

Inference of Vohradský's Models of Genetic Networks by Solving Two-Dimensional Function Optimization Problems

PubMed Central

Kimura, Shuhei; Sato, Masanao; Okada-Hatakeyama, Mariko

2013-01-01

The inference of a genetic network is a problem in which mutual interactions among genes are inferred from time-series of gene expression levels. While a number of models have been proposed to describe genetic networks, this study focuses on a mathematical model proposed by Vohradský. Because of its advantageous features, several researchers have proposed the inference methods based on Vohradský's model. When trying to analyze large-scale networks consisting of dozens of genes, however, these methods must solve high-dimensional non-linear function optimization problems. In order to resolve the difficulty of estimating the parameters of the Vohradský's model, this study proposes a new method that defines the problem as several two-dimensional function optimization problems. Through numerical experiments on artificial genetic network inference problems, we showed that, although the computation time of the proposed method is not the shortest, the method has the ability to estimate parameters of Vohradský's models more effectively with sufficiently short computation times. This study then applied the proposed method to an actual inference problem of the bacterial SOS DNA repair system, and succeeded in finding several reasonable regulations. PMID:24386175

Pathway activity inference for multiclass disease classification through a mathematical programming optimisation framework.

PubMed

Yang, Lingjian; Ainali, Chrysanthi; Tsoka, Sophia; Papageorgiou, Lazaros G

2014-12-05

Applying machine learning methods on microarray gene expression profiles for disease classification problems is a popular method to derive biomarkers, i.e. sets of genes that can predict disease state or outcome. Traditional approaches where expression of genes were treated independently suffer from low prediction accuracy and difficulty of biological interpretation. Current research efforts focus on integrating information on protein interactions through biochemical pathway datasets with expression profiles to propose pathway-based classifiers that can enhance disease diagnosis and prognosis. As most of the pathway activity inference methods in literature are either unsupervised or applied on two-class datasets, there is good scope to address such limitations by proposing novel methodologies. A supervised multiclass pathway activity inference method using optimisation techniques is reported. For each pathway expression dataset, patterns of its constituent genes are summarised into one composite feature, termed pathway activity, and a novel mathematical programming model is proposed to infer this feature as a weighted linear summation of expression of its constituent genes. Gene weights are determined by the optimisation model, in a way that the resulting pathway activity has the optimal discriminative power with regards to disease phenotypes. Classification is then performed on the resulting low-dimensional pathway activity profile. The model was evaluated through a variety of published gene expression profiles that cover different types of disease. We show that not only does it improve classification accuracy, but it can also perform well in multiclass disease datasets, a limitation of other approaches from the literature. Desirable features of the model include the ability to control the maximum number of genes that may participate in determining pathway activity, which may be pre-specified by the user. Overall, this work highlights the potential of building pathway-based multi-phenotype classifiers for accurate disease diagnosis and prognosis problems.

Cell-specific prediction and application of drug-induced gene expression profiles.

PubMed

Hodos, Rachel; Zhang, Ping; Lee, Hao-Chih; Duan, Qiaonan; Wang, Zichen; Clark, Neil R; Ma'ayan, Avi; Wang, Fei; Kidd, Brian; Hu, Jianying; Sontag, David; Dudley, Joel

2018-01-01

Gene expression profiling of in vitro drug perturbations is useful for many biomedical discovery applications including drug repurposing and elucidation of drug mechanisms. However, limited data availability across cell types has hindered our capacity to leverage or explore the cell-specificity of these perturbations. While recent efforts have generated a large number of drug perturbation profiles across a variety of human cell types, many gaps remain in this combinatorial drug-cell space. Hence, we asked whether it is possible to fill these gaps by predicting cell-specific drug perturbation profiles using available expression data from related conditions--i.e. from other drugs and cell types. We developed a computational framework that first arranges existing profiles into a three-dimensional array (or tensor) indexed by drugs, genes, and cell types, and then uses either local (nearest-neighbors) or global (tensor completion) information to predict unmeasured profiles. We evaluate prediction accuracy using a variety of metrics, and find that the two methods have complementary performance, each superior in different regions in the drug-cell space. Predictions achieve correlations of 0.68 with true values, and maintain accurate differentially expressed genes (AUC 0.81). Finally, we demonstrate that the predicted profiles add value for making downstream associations with drug targets and therapeutic classes.

Cell-specific prediction and application of drug-induced gene expression profiles

PubMed Central

Hodos, Rachel; Zhang, Ping; Lee, Hao-Chih; Duan, Qiaonan; Wang, Zichen; Clark, Neil R.; Ma'ayan, Avi; Wang, Fei; Kidd, Brian; Hu, Jianying; Sontag, David

2017-01-01

Gene expression profiling of in vitro drug perturbations is useful for many biomedical discovery applications including drug repurposing and elucidation of drug mechanisms. However, limited data availability across cell types has hindered our capacity to leverage or explore the cell-specificity of these perturbations. While recent efforts have generated a large number of drug perturbation profiles across a variety of human cell types, many gaps remain in this combinatorial drug-cell space. Hence, we asked whether it is possible to fill these gaps by predicting cell-specific drug perturbation profiles using available expression data from related conditions--i.e. from other drugs and cell types. We developed a computational framework that first arranges existing profiles into a three-dimensional array (or tensor) indexed by drugs, genes, and cell types, and then uses either local (nearest-neighbors) or global (tensor completion) information to predict unmeasured profiles. We evaluate prediction accuracy using a variety of metrics, and find that the two methods have complementary performance, each superior in different regions in the drug-cell space. Predictions achieve correlations of 0.68 with true values, and maintain accurate differentially expressed genes (AUC 0.81). Finally, we demonstrate that the predicted profiles add value for making downstream associations with drug targets and therapeutic classes. PMID:29218867

Three-dimensional culture of dental pulp stem cells in direct contact to tricalcium silicate cements.

PubMed

Widbiller, M; Lindner, S R; Buchalla, W; Eidt, A; Hiller, K-A; Schmalz, G; Galler, K M

2016-03-01

Calcium silicate cements are biocompatible dental materials applicable in contact with vital tissue. The novel tricalcium silicate cement Biodentine™ offers properties superior to commonly used mineral trioxide aggregate (MTA). Objective of this study was to evaluate its cytocompatibility and ability to induce differentiation and mineralization in three-dimensional cultures of dental pulp stem cells after direct contact with the material. Test materials included a new tricalcium silicate (Biodentine™, Septodont, Saint-Maur-des-Fossés, France), MTA (ProRoot® MTA, DENSPLY Tulsa Dental Specialities, Johnson City, TN, USA), glass ionomer (Ketac™ Molar Aplicap™, 3M ESPE, Seefeld, Germany), human dentin disks and polystyrene. Magnetic activated cell sorting for to the surface antigen STRO-1 was performed to gain a fraction enriched with mesenchymal stem cells. Samples were allowed to set and dental pulp stem cells in collagen carriers were placed on top. Scanning electron microscopy of tricalcium silicate cement surfaces with and without cells was conducted. Cell viability was measured for 14 days by MTT assay. Alkaline phosphatase activity was evaluated (days 3, 7, and 14) and expression of mineralization-associated genes (COL1A1, ALP, DSPP, and RUNX2) was quantified by real-time quantitative PCR. Nonparametric statistical analysis for cell viability and alkaline phosphatase data was performed to compare different materials as well as time points (Mann-Whitney U test, α = 0.05). Cell viability was highest on tricalcium silicate cement, followed by MTA. Viability on glass ionomer cement and dentin disks was significantly lower. Alkaline phosphatase activity was lower in cells on new tricalcium silicate cement compared to MTA, whereas expression patterns of marker genes were alike. Increased cell viability and similar levels of mineralization-associated gene expression in three-dimensional cell cultures on the novel tricalcium silicate cement and mineral trioxide aggregate indicate that the material is cytocompatible and bioactive. The tested new tricalcium silicate cement confirms its suitability as an alternative to MTA in vital pulp therapy.

Inflammatory Gene Regulatory Networks in Amnion Cells Following Cytokine Stimulation: Translational Systems Approach to Modeling Human Parturition

PubMed Central

Summerfield, Taryn L.; Yu, Lianbo; Gulati, Parul; Zhang, Jie; Huang, Kun; Romero, Roberto; Kniss, Douglas A.

2011-01-01

A majority of the studies examining the molecular regulation of human labor have been conducted using single gene approaches. While the technology to produce multi-dimensional datasets is readily available, the means for facile analysis of such data are limited. The objective of this study was to develop a systems approach to infer regulatory mechanisms governing global gene expression in cytokine-challenged cells in vitro, and to apply these methods to predict gene regulatory networks (GRNs) in intrauterine tissues during term parturition. To this end, microarray analysis was applied to human amnion mesenchymal cells (AMCs) stimulated with interleukin-1β, and differentially expressed transcripts were subjected to hierarchical clustering, temporal expression profiling, and motif enrichment analysis, from which a GRN was constructed. These methods were then applied to fetal membrane specimens collected in the absence or presence of spontaneous term labor. Analysis of cytokine-responsive genes in AMCs revealed a sterile immune response signature, with promoters enriched in response elements for several inflammation-associated transcription factors. In comparison to the fetal membrane dataset, there were 34 genes commonly upregulated, many of which were part of an acute inflammation gene expression signature. Binding motifs for nuclear factor-κB were prominent in the gene interaction and regulatory networks for both datasets; however, we found little evidence to support the utilization of pathogen-associated molecular pattern (PAMP) signaling. The tissue specimens were also enriched for transcripts governed by hypoxia-inducible factor. The approach presented here provides an uncomplicated means to infer global relationships among gene clusters involved in cellular responses to labor-associated signals. PMID:21655103

* Three-Dimensional Bioprinting of Polycaprolactone Reinforced Gene Activated Bioinks for Bone Tissue Engineering.

PubMed

Cunniffe, Gráinne M; Gonzalez-Fernandez, Tomas; Daly, Andrew; Sathy, Binulal N; Jeon, Oju; Alsberg, Eben; Kelly, Daniel J

2017-09-01

Regeneration of complex bone defects remains a significant clinical challenge. Multi-tool biofabrication has permitted the combination of various biomaterials to create multifaceted composites with tailorable mechanical properties and spatially controlled biological function. In this study we sought to use bioprinting to engineer nonviral gene activated constructs reinforced by polymeric micro-filaments. A gene activated bioink was developed using RGD-γ-irradiated alginate and nano-hydroxyapatite (nHA) complexed to plasmid DNA (pDNA). This ink was combined with bone marrow-derived mesenchymal stem cells (MSCs) and then co-printed with a polycaprolactone supporting mesh to provide mechanical stability to the construct. Reporter genes were first used to demonstrate successful cell transfection using this system, with sustained expression of the transgene detected over 14 days postbioprinting. Delivery of a combination of therapeutic genes encoding for bone morphogenic protein and transforming growth factor promoted robust osteogenesis of encapsulated MSCs in vitro, with enhanced levels of matrix deposition and mineralization observed following the incorporation of therapeutic pDNA. Gene activated MSC-laden constructs were then implanted subcutaneously, directly postfabrication, and were found to support superior levels of vascularization and mineralization compared to cell-free controls. These results validate the use of a gene activated bioink to impart biological functionality to three-dimensional bioprinted constructs.

Association Between Germline Mutation in VSIG10L and Familial Barrett Neoplasia.

PubMed

Fecteau, Ryan E; Kong, Jianping; Kresak, Adam; Brock, Wendy; Song, Yeunjoo; Fujioka, Hisashi; Elston, Robert; Willis, Joseph E; Lynch, John P; Markowitz, Sanford D; Guda, Kishore; Chak, Amitabh

2016-10-01

Esophageal adenocarcinoma and its precursor lesion Barrett esophagus have seen a dramatic increase in incidence over the past 4 decades yet marked genetic heterogeneity of this disease has precluded advances in understanding its pathogenesis and improving treatment. To identify novel disease susceptibility variants in a familial syndrome of esophageal adenocarcinoma and Barrett esophagus, termed familial Barrett esophagus, by using high-throughput sequencing in affected individuals from a large, multigenerational family. We performed whole exome sequencing (WES) from peripheral lymphocyte DNA on 4 distant relatives from our multiplex, multigenerational familial Barrett esophagus family to identify candidate disease susceptibility variants. Gene variants were filtered, verified, and segregation analysis performed to identify a single candidate variant. Gene expression analysis was done with both quantitative real-time polymerase chain reaction and in situ RNA hybridization. A 3-dimensional organotypic cell culture model of esophageal maturation was utilized to determine the phenotypic effects of our gene variant. We used electron microscopy on esophageal mucosa from an affected family member carrying the gene variant to assess ultrastructural changes. Identification of a novel, germline disease susceptibility variant in a previously uncharacterized gene. A multiplex, multigenerational family with 14 members affected (3 members with esophageal adenocarcinoma and 11 with Barrett esophagus) was identified, and whole-exome sequencing identified a germline mutation (S631G) at a highly conserved serine residue in the uncharacterized gene VSIG10L that segregated in affected members. Transfection of S631G variant into a 3-dimensional organotypic culture model of normal esophageal squamous cells dramatically inhibited epithelial maturation compared with the wild-type. VSIG10L exhibited high expression in normal squamous esophagus with marked loss of expression in Barrett-associated lesions. Electron microscopy of squamous esophageal mucosa harboring the S631G variant revealed dilated intercellular spaces and reduced desmosomes. This study presents VSIG10L as a candidate familial Barrett esophagus susceptibility gene, with a putative role in maintaining normal esophageal homeostasis. Further research assessing VSIG10L function may reveal pathways important for esophageal maturation and the pathogenesis of Barrett esophagus and esophageal adenocarcinoma.

Association Between Germline Mutation in VSIG10L and Familial Barrett Neoplasia

PubMed Central

Fecteau, Ryan E.; Kong, Jianping; Kresak, Adam; Brock, Wendy; Song, Yeunjoo; Fujioka, Hisashi; Elston, Robert; Willis, Joseph E.; Lynch, John P.; Markowitz, Sanford D.; Guda, Kishore; Chak, Amitabh

2016-01-01

IMPORTANCE Esophageal adenocarcinoma and its precursor lesion Barrett esophagus have seen a dramatic increase in incidence over the past 4 decades yet marked genetic heterogeneity of this disease has precluded advances in understanding its pathogenesis and improving treatment. OBJECTIVE To identify novel disease susceptibility variants in a familial syndrome of esophageal adenocarcinoma and Barrett esophagus, termed familial Barrett esophagus, by using high-throughput sequencing in affected individuals from a large, multigenerational family. DESIGN, SETTING, AND PARTICIPANTS We performed whole exome sequencing (WES) from peripheral lymphocyte DNA on 4 distant relatives from our multiplex, multigenerational familial Barrett esophagus family to identify candidate disease susceptibility variants. Gene variants were filtered, verified, and segregation analysis performed to identify a single candidate variant. Gene expression analysis was done with both quantitative real-time polymerase chain reaction and in situ RNA hybridization. A 3-dimensional organotypic cell culture model of esophageal maturation was utilized to determine the phenotypic effects of our gene variant. We used electron microscopy on esophageal mucosa from an affected family member carrying the gene variant to assess ultrastructural changes. MAIN OUTCOMES AND MEASURES Identification of a novel, germline disease susceptibility variant in a previously uncharacterized gene. RESULTS A multiplex, multigenerational family with 14 members affected (3 members with esophageal adenocarcinoma and 11 with Barrett esophagus) was identified, and whole-exome sequencing identified a germline mutation (S631G) at a highly conserved serine residue in the uncharacterized gene VSIG10L that segregated in affected members. Transfection of S631G variant into a 3-dimensional organotypic culture model of normal esophageal squamous cells dramatically inhibited epithelial maturation compared with the wild-type. VSIG10L exhibited high expression in normal squamous esophagus with marked loss of expression in Barrett-associated lesions. Electron microscopy of squamous esophageal mucosa harboring the S631G variant revealed dilated intercellular spaces and reduced desmosomes. CONCLUSIONS AND RELEVANCE This study presents VSIG10L as a candidate familial Barrett esophagus susceptibility gene, with a putative role in maintaining normal esophageal homeostasis. Further research assessing VSIG10L function may reveal pathways important for esophageal maturation and the pathogenesis of Barrett esophagus and esophageal adenocarcinoma. PMID:27467440

Mechanisms of gap gene expression canalization in the Drosophila blastoderm.

PubMed

Gursky, Vitaly V; Panok, Lena; Myasnikova, Ekaterina M; Manu; Samsonova, Maria G; Reinitz, John; Samsonov, Alexander M

2011-01-01

Extensive variation in early gap gene expression in the Drosophila blastoderm is reduced over time because of gap gene cross regulation. This phenomenon is a manifestation of canalization, the ability of an organism to produce a consistent phenotype despite variations in genotype or environment. The canalization of gap gene expression can be understood as arising from the actions of attractors in the gap gene dynamical system. In order to better understand the processes of developmental robustness and canalization in the early Drosophila embryo, we investigated the dynamical effects of varying spatial profiles of Bicoid protein concentration on the formation of the expression border of the gap gene hunchback. At several positions on the anterior-posterior axis of the embryo, we analyzed attractors and their basins of attraction in a dynamical model describing expression of four gap genes with the Bicoid concentration profile accounted as a given input in the model equations. This model was tested against a family of Bicoid gradients obtained from individual embryos. These gradients were normalized by two independent methods, which are based on distinct biological hypotheses and provide different magnitudes for Bicoid spatial variability. We showed how the border formation is dictated by the biological initial conditions (the concentration gradient of maternal Hunchback protein) being attracted to specific attracting sets in a local vicinity of the border. Different types of these attracting sets (point attractors or one dimensional attracting manifolds) define several possible mechanisms of border formation. The hunchback border formation is associated with intersection of the spatial gradient of the maternal Hunchback protein and a boundary between the attraction basins of two different point attractors. We demonstrated how the positional variability for hunchback is related to the corresponding variability of the basin boundaries. The observed reduction in variability of the hunchback gene expression can be accounted for by specific geometrical properties of the basin boundaries. We clarified the mechanisms of gap gene expression canalization in early Drosophila embryos. These mechanisms were specified in the case of hunchback in well defined terms of the dynamical system theory.

Gene expression based mouse brain parcellation using Markov random field regularized non-negative matrix factorization

NASA Astrophysics Data System (ADS)

Pathak, Sayan D.; Haynor, David R.; Thompson, Carol L.; Lein, Ed; Hawrylycz, Michael

2009-02-01

Understanding the geography of genetic expression in the mouse brain has opened previously unexplored avenues in neuroinformatics. The Allen Brain Atlas (www.brain-map.org) (ABA) provides genome-wide colorimetric in situ hybridization (ISH) gene expression images at high spatial resolution, all mapped to a common three-dimensional 200μm3 spatial framework defined by the Allen Reference Atlas (ARA) and is a unique data set for studying expression based structural and functional organization of the brain. The goal of this study was to facilitate an unbiased data-driven structural partitioning of the major structures in the mouse brain. We have developed an algorithm that uses nonnegative matrix factorization (NMF) to perform parts based analysis of ISH gene expression images. The standard NMF approach and its variants are limited in their ability to flexibly integrate prior knowledge, in the context of spatial data. In this paper, we introduce spatial connectivity as an additional regularization in NMF decomposition via the use of Markov Random Fields (mNMF). The mNMF algorithm alternates neighborhood updates with iterations of the standard NMF algorithm to exploit spatial correlations in the data. We present the algorithm and show the sub-divisions of hippocampus and somatosensory-cortex obtained via this approach. The results are compared with established neuroanatomic knowledge. We also highlight novel gene expression based sub divisions of the hippocampus identified by using the mNMF algorithm.

Human endothelial cell growth and phenotypic expression on three dimensional poly(lactide-co-glycolide) sintered microsphere scaffolds for bone tissue engineering.

PubMed

Jabbarzadeh, Ehsan; Jiang, Tao; Deng, Meng; Nair, Lakshmi S; Khan, Yusuf M; Laurencin, Cato T

2007-12-01

Bone tissue engineering offers promising alternatives to repair and restore tissues. Our laboratory has employed poly(lactide-co-glycolide) PLAGA microspheres to develop a three dimensional (3-D) porous bioresorbable scaffold with a biomimetic pore structure. Osseous healing and integration with the surrounding tissue depends in part on new blood vessel formation within the porous structure. Since endothelial cells play a key role in angiogenesis (formation of new blood vessels from pre-existing vasculature), the purpose of this study was to better understand human endothelial cell attachment, viability, growth, and phenotypic expression on sintered PLAGA microsphere scaffold. Scanning electron microscopy (SEM) examination showed cells attaching to the surface of microspheres and bridging the pores between the microspheres. Cell proliferation studies indicated that cell number increased during early stages and reached a plateau between days 10 and 14. Immunofluorescent staining for actin showed that cells were proliferating three dimensionally through the scaffolds while staining for PECAM-1 (platelet endothelial cell adhesion molecule) displayed typical localization at cell-cell contacts. Gene expression analysis showed that endothelial cells grown on PLAGA scaffolds maintained their normal characteristic phenotype. The cell proliferation and phenotypic expression were independent of scaffold pore architecture. These results demonstrate that PLAGA sintered microsphere scaffolds can support the growth and biological functions of human endothelial cells. The insights from this study should aid future studies aimed at enhancing angiogenesis in three dimensional tissue engineered scaffolds.

Evolution of robustness to damage in artificial 3-dimensional development.

PubMed

Joachimczak, Michał; Wróbel, Borys

2012-09-01

GReaNs is an Artificial Life platform we have built to investigate the general principles that guide evolution of multicellular development and evolution of artificial gene regulatory networks. The embryos develop in GReaNs in a continuous 3-dimensional (3D) space with simple physics. The developmental trajectories are indirectly encoded in linear genomes. The genomes are not limited in size and determine the topology of gene regulatory networks that are not limited in the number of nodes. The expression of the genes is continuous and can be modified by adding environmental noise. In this paper we evolved development of structures with a specific shape (an ellipsoid) and asymmetrical pattering (a 3D pattern inspired by the French flag problem), and investigated emergence of the robustness to damage in development and the emergence of the robustness to noise. Our results indicate that both types of robustness are related, and that including noise during evolution promotes higher robustness to damage. Interestingly, we have observed that some evolved gene regulatory networks rely on noise for proper behaviour. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Exploring multicollinearity using a random matrix theory approach.

PubMed

Feher, Kristen; Whelan, James; Müller, Samuel

2012-01-01

Clustering of gene expression data is often done with the latent aim of dimension reduction, by finding groups of genes that have a common response to potentially unknown stimuli. However, what is poorly understood to date is the behaviour of a low dimensional signal embedded in high dimensions. This paper introduces a multicollinear model which is based on random matrix theory results, and shows potential for the characterisation of a gene cluster's correlation matrix. This model projects a one dimensional signal into many dimensions and is based on the spiked covariance model, but rather characterises the behaviour of the corresponding correlation matrix. The eigenspectrum of the correlation matrix is empirically examined by simulation, under the addition of noise to the original signal. The simulation results are then used to propose a dimension estimation procedure of clusters from data. Moreover, the simulation results warn against considering pairwise correlations in isolation, as the model provides a mechanism whereby a pair of genes with `low' correlation may simply be due to the interaction of high dimension and noise. Instead, collective information about all the variables is given by the eigenspectrum.

Pea amyloplast DNA is qualitatively similar to pea chloroplast DNA

NASA Technical Reports Server (NTRS)

Gaynor, J. J.

1984-01-01

Amyloplast DNA (apDNA), when subjected to digestion with restriction endonucleases, yields patterns nearly identical to that of DNA from mature pea chloroplasts (ctDNA). Southern transfers of apDNA and ctDNA, probed with the large subunit (LS) gene of ribulose-1,5-bisphosphate carboxylase (Rubisco), shows hybridization to the expected restriction fragments for both apDNA and ctDNA. However, Northern transfers of total RNA from chloroplasts and amyloplasts, probed again with the LS gene of Rubisco, shows that no detectable LS meggage is found in amyloplasts although LS expression in mature chloroplasts is high. Likewise, two dimensional polyacrylamide gel electrophoresis of etiolated gravisensitive pea tissue shows that both large and small subunits of Rubisco are conspicuously absent; however, in greening tissue these two constitute the major soluble proteins. These findings suggest that although the informational content of these two organelle types is equivalent, gene expression is quite different and is presumably under nuclear control.

Telomeric repeat-containing RNA/G-quadruplex-forming sequences cause genome-wide alteration of gene expression in human cancer cells in vivo.

PubMed

Hirashima, Kyotaro; Seimiya, Hiroyuki

2015-02-27

Telomere erosion causes cell mortality, suggesting that longer telomeres enable more cell divisions. In telomerase-positive human cancer cells, however, telomeres are often kept shorter than those of surrounding normal tissues. Recently, we showed that cancer cell telomere elongation represses innate immune genes and promotes their differentiation in vivo. This implies that short telomeres contribute to cancer malignancy, but it is unclear how such genetic repression is caused by elongated telomeres. Here, we report that telomeric repeat-containing RNA (TERRA) induces a genome-wide alteration of gene expression in telomere-elongated cancer cells. Using three different cell lines, we found that telomere elongation up-regulates TERRA signal and down-regulates innate immune genes such as STAT1, ISG15 and OAS3 in vivo. Ectopic TERRA oligonucleotides repressed these genes even in cells with short telomeres under three-dimensional culture conditions. This appeared to occur from the action of G-quadruplexes (G4) in TERRA, because control oligonucleotides had no effect and a nontelomeric G4-forming oligonucleotide phenocopied the TERRA oligonucleotide. Telomere elongation and G4-forming oligonucleotides showed similar gene expression signatures. Most of the commonly suppressed genes were involved in the innate immune system and were up-regulated in various cancers. We propose that TERRA G4 counteracts cancer malignancy by suppressing innate immune genes. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Nuclear organization mediates cancer-compromised genetic and epigenetic control.

PubMed

Zaidi, Sayyed K; Fritz, Andrew; Tracy, Kirsten; Gordon, Jonathan; Tye, Coralee; Boyd, Joseph; Van Wijnen, Andre; Nickerson, Jeffrey; Imbalzano, Anthony; Lian, Jane; Stein, Janet; Stein, Gary

2018-05-09

Nuclear organization is functionally linked to genetic and epigenetic regulation of gene expression for biological control and is modified in cancer. Nuclear organization supports cell growth and phenotypic properties of normal and cancer cells by facilitating physiologically responsive interactions of chromosomes, genes and regulatory complexes at dynamic three-dimensional microenvironments. We will review nuclear structure/function relationships that include: 1. Epigenetic bookmarking of genes by phenotypic transcription factors to control fidelity and plasticity of gene expression as cells enter and exit mitosis; 2. Contributions of chromatin remodeling to breast cancer nuclear morphology, metabolism and effectiveness of chemotherapy; 3. Relationships between fidelity of nuclear organization and metastasis of breast cancer to bone; 4. Dynamic modifications of higher-order inter- and intra-chromosomal interactions in breast cancer cells; 5. Coordinate control of cell growth and phenotype by tissue-specific transcription factors; 6. Oncofetal epigenetic control by bivalent histone modifications that are functionally related to sustaining the stem cell phenotype; and 7. Noncoding RNA-mediated regulation in the onset and progression of breast cancer. The discovery of components to nuclear organization that are functionally related to cancer and compromise gene expression have the potential for translation to innovative cancer diagnosis and targeted therapy. Copyright © 2018 Elsevier Ltd. All rights reserved.

The three-dimensional architecture of a bacterial genome and its alteration by genetic perturbation.

PubMed

Umbarger, Mark A; Toro, Esteban; Wright, Matthew A; Porreca, Gregory J; Baù, Davide; Hong, Sun-Hae; Fero, Michael J; Zhu, Lihua J; Marti-Renom, Marc A; McAdams, Harley H; Shapiro, Lucy; Dekker, Job; Church, George M

2011-10-21

We have determined the three-dimensional (3D) architecture of the Caulobacter crescentus genome by combining genome-wide chromatin interaction detection, live-cell imaging, and computational modeling. Using chromosome conformation capture carbon copy (5C), we derive ~13 kb resolution 3D models of the Caulobacter genome. The resulting models illustrate that the genome is ellipsoidal with periodically arranged arms. The parS sites, a pair of short contiguous sequence elements known to be involved in chromosome segregation, are positioned at one pole, where they anchor the chromosome to the cell and contribute to the formation of a compact chromatin conformation. Repositioning these elements resulted in rotations of the chromosome that changed the subcellular positions of most genes. Such rotations did not lead to large-scale changes in gene expression, indicating that genome folding does not strongly affect gene regulation. Collectively, our data suggest that genome folding is globally dictated by the parS sites and chromosome segregation. Copyright © 2011 Elsevier Inc. All rights reserved.

Human Gingival Fibroblasts Display a Non-Fibrotic Phenotype Distinct from Skin Fibroblasts in Three-Dimensional Cultures

PubMed Central

Mah, Wesley; Jiang, Guoqiao; Olver, Dylan; Cheung, Godwin; Kim, Ben; Larjava, Hannu; Häkkinen, Lari

2014-01-01

Scar formation following skin injury can be a major psychosocial and physiological problem. However, the mechanisms of scar formation are still not completely understood. Previous studies have shown that wound healing in oral mucosa is faster, associates with a reduced inflammatory response and results to significantly reduced scar formation compared with skin wounds. In the present study, we hypothesized that oral mucosal fibroblasts from human gingiva are inherently distinct from fibroblasts from breast and abdominal skin, two areas prone to excessive scar formation, which may contribute to the preferential wound healing outcome in gingiva. To this end, we compared the phenotype of human gingival and skin fibroblasts cultured in in vivo-like three-dimensional (3D) cultures that mimic the cells' natural extracellular matrix (ECM) niche. To establish 3D cultures, five parallel fibroblast lines from human gingiva (GFBLs) and breast skin (SFBLs) were seeded in high density, and cultured for up to 21 days in serum and ascorbic acid containing medium to induce expression of wound-healing transcriptome and ECM deposition. Cell proliferation, morphology, phenotype and expression of wound healing and scar related genes were analyzed by real-time RT-PCR, Western blotting and immunocytochemical methods. The expression of a set of genes was also studied in three parallel lines of human abdominal SFBLs. Findings showed that GFBLs displayed morphologically distinct organization of the 3D cultures and proliferated faster than SFBLs. GFBLs expressed elevated levels of molecules involved in regulation of inflammation and ECM remodeling (MMPs) while SFBLs showed significantly higher expression of TGF-β signaling, ECM and myofibroblast and cell contractility-related genes. Thus, GFBLs display an inherent phenotype conducive for fast resolution of inflammation and ECM remodeling, characteristic for scar-free wound healing, while SFBLs have a profibrotic, scar-prone phenotype. PMID:24608113

LHP1 Regulates H3K27me3 Spreading and Shapes the Three-Dimensional Conformation of the Arabidopsis Genome

PubMed Central

Ariel, Federico; Latrasse, David; Mariappan, Kiruthiga Gayathri; Kim, Soon-Kap; Crespi, Martin; Hirt, Heribert; Bergounioux, Catherine; Raynaud, Cécile; Benhamed, Moussa

2016-01-01

Precise expression patterns of genes in time and space are essential for proper development of multicellular organisms. Dynamic chromatin conformation and spatial organization of the genome constitute a major step in this regulation to modulate developmental outputs. Polycomb repressive complexes (PRCs) mediate stable or flexible gene repression in response to internal and environmental cues. In Arabidopsis thaliana, LHP1 co-localizes with H3K27me3 epigenetic marks throughout the genome and interacts with PRC1 and PRC2 members as well as with a long noncoding RNA. Here, we show that LHP1 is responsible for the spreading of H3K27me3 towards the 3’ end of the gene body. We also identified a subset of LHP1-activated genes and demonstrated that LHP1 shapes local chromatin topology in order to control transcriptional co-regulation. Our work reveals a general role of LHP1 from local to higher conformation levels of chromatin configuration to determine its accessibility to define gene expression patterns. PMID:27410265

Reconstruction of Hyaline Cartilage Deep Layer Properties in 3-Dimensional Cultures of Human Articular Chondrocytes.

PubMed

Nanduri, Vibudha; Tattikota, Surendra Mohan; T, Avinash Raj; Sriramagiri, Vijaya Rama Rao; Kantipudi, Suma; Pande, Gopal

2014-06-01

Articular cartilage (AC) injuries and malformations are commonly noticed because of trauma or age-related degeneration. Many methods have been adopted for replacing or repairing the damaged tissue. Currently available AC repair methods, in several cases, fail to yield good-quality long-lasting results, perhaps because the reconstructed tissue lacks the cellular and matrix properties seen in hyaline cartilage (HC). To reconstruct HC tissue from 2-dimensional (2D) and 3-dimensional (3D) cultures of AC-derived human chondrocytes that would specifically exhibit the cellular and biochemical properties of the deep layer of HC. Descriptive laboratory study. Two-dimensional cultures of human AC-derived chondrocytes were established in classical medium (CM) and newly defined medium (NDM) and maintained for a period of 6 weeks. These cells were suspended in 2 mm-thick collagen I gels, placed in 24-well culture inserts, and further cultured up to 30 days. Properties of chondrocytes, grown in 2D cultures and the reconstructed 3D cartilage tissue, were studied by optical and scanning electron microscopic techniques, immunohistochemistry, and cartilage-specific gene expression profiling by reverse transcription polymerase chain reaction and were compared with those of the deep layer of native human AC. Two-dimensional chondrocyte cultures grown in NDM, in comparison with those grown in CM, showed more chondrocyte-specific gene activity and matrix properties. The NDM-grown chondrocytes in 3D cultures also showed better reproduction of deep layer properties of HC, as confirmed by microscopic and gene expression analysis. The method used in this study can yield cartilage tissue up to approximately 1.6 cm in diameter and 2 mm in thickness that satisfies the very low cell density and matrix composition properties present in the deep layer of normal HC. This study presents a novel and reproducible method for long-term culture of AC-derived chondrocytes and reconstruction of cartilage tissue with properties similar to the deep layer of HC in vitro. The HC tissue obtained by the method described can be used to develop an implantable product for the replacement of damaged or malformed AC, especially in younger patients where the lesions are caused by trauma or mechanical stress.

High-Dimensional Gene Expression Profiling Studies in High and Low Responders to Primary Smallpox Vaccination

PubMed Central

Haralambieva, Iana H.; Oberg, Ann L.; Dhiman, Neelam; Ovsyannikova, Inna G.; Kennedy, Richard B.; Grill, Diane E.; Jacobson, Robert M.; Poland, Gregory A.

2012-01-01

Background. The mechanisms underlying smallpox vaccine-induced variations in immune responses are not well understood, but are of considerable interest to a deeper understanding of poxvirus immunity and correlates of protection. Methods. We assessed transcriptional messenger RNA expression changes in 197 recipients of primary smallpox vaccination representing the extremes of humoral and cellular immune responses. Results. The 20 most significant differentially expressed genes include a tumor necrosis factor–receptor superfamily member, an interferon (IFN) gene, a chemokine gene, zinc finger protein genes, nuclear factors, and histones (P ≤ 1.06E−20, q ≤ 2.64E−17). A pathway analysis identified 4 enriched pathways with cytokine production by the T-helper 17 subset of CD4+ T cells being the most significant pathway (P = 3.42E−05). Two pathways (antiviral actions of IFNs, P = 8.95E−05; and IFN-α/β signaling pathway, P = 2.92E−04), integral to innate immunity, were enriched when comparing high with low antibody responders (false discovery rate, < 0.05). Genes related to immune function and transcription (TLR8, P = .0002; DAPP1, P = .0003; LAMP3, P = 9.96E−05; NR4A2, P ≤ .0002; EGR3, P = 4.52E−05), and other genes with a possible impact on immunity (LNPEP, P = 3.72E−05; CAPRIN1, P = .0001; XRN1, P = .0001), were found to be expressed differentially in high versus low antibody responders. Conclusion. We identified novel and known immunity-related genes and pathways that may account for differences in immune response to smallpox vaccination. PMID:22949304

An inherited FGFR2 mutation increased osteogenesis gene expression and result in Crouzon syndrome.

PubMed

Fan, Jiayan; Li, Yinwei; Jia, Renbing; Fan, Xianqun

2018-05-30

FGFR2 encodes a fibroblast growth factor receptor whose mutations are responsible for the Crouzon syndrome, involving craniosynostosis and facial dysostosis with shallow orbits. However, few reports are available quantifying the orbital volume of Crouzon syndrome and there was little direct evidence to show FGFR2 mutation actually influencing orbital morphology. Ten Crouzon syndrome patients underwent a standard ophthalmologic assessment. Morphology study was carried out based on 3-dimensional computed tomography scan to calculate orbital volume. Genomic DNA was extracted from peripheral blood leukocytes of the patients and genomic screening of FGFR2. A three-dimensional computer model was used to analyse the structural positioning of the mutation site that was predicted possible impact on functional of FGFR2 protein. Real-time PCR was performed to analyse the expression of bone maker gene. We describe a FGFR2 mutation (p.G338R, c.1012G > C) in a Chinese family with Crouzon syndrome. Computational analysis showed the mutate protein obviously changes in the local spatial structure compared with wild-type FGFR2. The expression of osteocalcin and alkaline phosphatase two osteoblast specific genes significantly increased in orbital bone directly from patient compared to normal individual, which may lead to facial dysostosis. This is compatible with the shallow and round orbits in our Crouzon syndrome patient. Our study further identified G338R FGFR2 mutation (c1012G > C) lead to inherited Crouzon syndrome. Thus, early intervention, both medically and surgically, as well as disciplined by a multiple interdisciplinary teams are crucial to the management of this disorder.

Changes in gene expression, protein content and morphology of chondrocytes cultured on a 3D Random Positioning Machine and 2D rotating clinostat

NASA Astrophysics Data System (ADS)

Aleshcheva, Ganna; Hauslage, Jens; Hemmersbach, Ruth; Infanger, Manfred; Bauer, Johann; Grimm, Daniela; Sahana, Jayashree

Chondrocytes are the only cell type found in human cartilage consisting of proteoglycans and type II collagen. Several studies on chondrocytes cultured either in Space or on a ground-based facility for simulation of microgravity revealed that these cells are very resistant to adverse effects and stress induced by altered gravity. Tissue engineering of chondrocytes is a new strategy for cartilage regeneration. Using a three-dimensional Random Positioning Machine and a 2D rotating clinostat, devices designed to simulate microgravity on Earth, we investigated the early effects of microgravity exposure on human chondrocytes of six different donors after 30 min, 2 h, 4 h, 16 h, and 24 h and compared the results with the corresponding static controls cultured under normal gravity conditions. As little as 30 min of exposure resulted in increased expression of several genes responsible for cell motility, structure and integrity (beta-actin); control of cell growth, cell proliferation, cell differentiation and apoptosis; and cytoskeletal components such as microtubules (beta-tubulin) and intermediate filaments (vimentin). After 4 hours disruptions in the vimentin network were detected. These changes were less dramatic after 16 hours, when human chondrocytes appeared to reorganize their cytoskeleton. However, the gene expression and protein content of TGF-β1 was enhanced for 24 h. Based on the results achieved, we suggest that chondrocytes exposed to simulated microgravity seem to change their extracellular matrix production behavior while they rearrange their cytoskeletal proteins prior to forming three-dimensional aggregates.

Decoding the Regulatory Network for Blood Development from Single-Cell Gene Expression Measurements

PubMed Central

Haghverdi, Laleh; Lilly, Andrew J.; Tanaka, Yosuke; Wilkinson, Adam C.; Buettner, Florian; Macaulay, Iain C.; Jawaid, Wajid; Diamanti, Evangelia; Nishikawa, Shin-Ichi; Piterman, Nir; Kouskoff, Valerie; Theis, Fabian J.; Fisher, Jasmin; Göttgens, Berthold

2015-01-01

Here we report the use of diffusion maps and network synthesis from state transition graphs to better understand developmental pathways from single cell gene expression profiling. We map the progression of mesoderm towards blood in the mouse by single-cell expression analysis of 3,934 cells, capturing cells with blood-forming potential at four sequential developmental stages. By adapting the diffusion plot methodology for dimensionality reduction to single-cell data, we reconstruct the developmental journey to blood at single-cell resolution. Using transitions between individual cellular states as input, we develop a single-cell network synthesis toolkit to generate a computationally executable transcriptional regulatory network model that recapitulates blood development. Model predictions were validated by showing that Sox7 inhibits primitive erythropoiesis, and that Sox and Hox factors control early expression of Erg. We therefore demonstrate that single-cell analysis of a developing organ coupled with computational approaches can reveal the transcriptional programs that control organogenesis. PMID:25664528

Multiple mechanisms underlie defective recognition of melanoma cells cultured in three-dimensional architectures by antigen-specific cytotoxic T lymphocytes.

PubMed

Feder-Mengus, C; Ghosh, S; Weber, W P; Wyler, S; Zajac, P; Terracciano, L; Oertli, D; Heberer, M; Martin, I; Spagnoli, G C; Reschner, A

2007-04-10

Cancer cells' growth in three-dimensional (3D) architectures promotes resistance to drugs, cytokines, or irradiation. We investigated effects of 3D culture as compared to monolayers (2D) on melanoma cells' recognition by tumour-associated antigen (TAA)-specific HLA-A(*)0201-restricted cytotoxic T-lymphocytes (CTL). Culture of HBL, D10 (both HLA-A(*)0201+, TAA+) and NA8 (HLA-A(*)0201+, TAA-) melanoma cells on polyHEMA-coated plates, resulted in generation of 3D multicellular tumour spheroids (MCTS). Interferon-gamma (IFN-gamma) production by HLA-A(*)0201-restricted Melan-A/MART-1(27-35) or gp 100(280-288)-specific CTL clones served as immunorecognition marker. Co-culture with melanoma MCTS, resulted in defective TAA recognition by CTL as compared to 2D as witnessed by decreased IFN-gamma production and decreased Fas Ligand, perforin and granzyme B gene expression. A multiplicity of mechanisms were potentially involved. First, MCTS per se limit CTL capacity of recognising HLA class I restricted antigens by reducing exposed cell surfaces. Second, expression of melanoma differentiation antigens is downregulated in MCTS. Third, expression of HLA class I molecules can be downregulated in melanoma MCTS, possibly due to decreased interferon-regulating factor-1 gene expression. Fourth, lactic acid production is increased in MCTS, as compared to 2D. These data suggest that melanoma cells growing in 3D, even in the absence of immune selection, feature characteristics capable of dramatically inhibiting TAA recognition by specific CTL.

Tissue specificity of the hormonal response in sex accessory tissues is associated with nuclear matrix protein patterns.

PubMed

Getzenberg, R H; Coffey, D S

1990-09-01

The DNA of interphase nuclei have very specific three-dimensional organizations that are different in different cell types, and it is possible that this varying DNA organization is responsible for the tissue specificity of gene expression. The nuclear matrix organizes the three-dimensional structure of the DNA and is believed to be involved in the control of gene expression. This study compares the nuclear structural proteins between two sex accessory tissues in the same animal responding to the same androgen stimulation by the differential expression of major tissue-specific secretory proteins. We demonstrate here that the nuclear matrix is tissue specific in the rat ventral prostate and seminal vesicle, and undergoes characteristic alterations in its protein composition upon androgen withdrawal. Three types of nuclear matrix proteins were observed: 1) nuclear matrix proteins that are different and tissue specific in the rat ventral prostate and seminal vesicle, 2) a set of nuclear matrix proteins that either appear or disappear upon androgen withdrawal, and 3) a set of proteins that are common to both the ventral prostate and seminal vesicle and do not change with the hormonal state of the animal. Since the nuclear matrix is known to bind androgen receptors in a tissue- and steroid-specific manner, we propose that the tissue specificity of the nuclear matrix arranges the DNA in a unique conformation, which may be involved in the specific interaction of transcription factors with DNA sequences, resulting in tissue-specific patterns of secretory protein expression.

Integration of transcriptomic and cytoarchitectonic data implicates a role for MAOA and TAC1 in the limbic-cortical network.

PubMed

Bludau, Sebastian; Mühleisen, Thomas W; Eickhoff, Simon B; Hawrylycz, Michael J; Cichon, Sven; Amunts, Katrin

2018-06-01

Decoding the chain from genes to cognition requires detailed insights how areas with specific gene activities and microanatomical architectures contribute to brain function and dysfunction. The Allen Human Brain Atlas contains regional gene expression data, while the JuBrain Atlas offers three-dimensional cytoarchitectonic maps reflecting interindividual variability. To date, an integrated framework that combines the analytical benefits of both scientific platforms towards a multi-level brain atlas of adult humans was not available. We have, therefore, developed JuGEx, a new method for integrating tissue transcriptome and cytoarchitectonic segregation. We investigated differential gene expression in two JuBrain areas of the frontal pole that we have structurally and functionally characterized in previous studies. Our results show a significant upregulation of MAOA and TAC1 in the medial area frontopolaris which is a node in the limbic-cortical network and known to be susceptible for gray matter loss and behavioral dysfunction in patients with depression. The MAOA gene encodes an enzyme which is involved in the catabolism of dopamine, norepinephrine, serotonin, and other monoaminergic neurotransmitters. The TAC1 locus generates hormones that play a role in neuron excitations and behavioral responses. Overall, JuGEx provides a new tool for the scientific community that empowers research from basic, cognitive and clinical neuroscience in brain regions and disease models with regard to gene expression.

Surfactant Protein–C Chromatin-Bound Green Fluorescence Protein Reporter Mice Reveal Heterogeneity of Surfactant Protein C–Expressing Lung Cells

PubMed Central

Lee, Joo-Hyeon; Kim, Jonghwan; Gludish, David; Roach, Rebecca R.; Saunders, Arven H.; Barrios, Juliana; Woo, Andrew Jonghan; Chen, Huaiyong; Conner, David A.; Fujiwara, Yuko; Stripp, Barry R.

2013-01-01

The regeneration of alveolar epithelial cells is a critical aspect of alveolar reorganization after lung injury. Although alveolar Type II (AT2) cells have been described as progenitor cells for alveolar epithelia, more remains to be understood about how their progenitor cell properties are regulated. A nuclear, chromatin-bound green fluorescence protein reporter (H2B-GFP) was driven from the murine surfactant protein–C (SPC) promoter to generate SPC H2B-GFP transgenic mice. The SPC H2B-GFP allele allowed the FACS-based enrichment and gene expression profiling of AT2 cells. Approximately 97% of AT2 cells were GFP-labeled on Postnatal Day 1, and the percentage of GFP-labeled AT2 cells decreased to approximately 63% at Postnatal Week 8. Isolated young adult SPC H2B-GFP+ cells displayed proliferation, differentiation, and self-renewal capacity in the presence of lung fibroblasts in a Matrigel-based three-dimensional culture system. Heterogeneity within the GFP+ population was revealed, because cells with distinct alveolar and bronchiolar gene expression arose in three-dimensional cultures. CD74, a surface marker highly enriched on GFP+ cells, was identified as a positive selection marker, providing 3-fold enrichment for AT2 cells. In vivo, GFP expression was induced within other epithelial cell types during maturation of the distal lung. The utility of the SPC H2B-GFP murine model for the identification of AT2 cells was greatest in early postnatal lungs and more limited with age, when some discordance between SPC and GFP expression was observed. In adult mice, this allele may allow for the enrichment and future characterization of other SPC-expressing alveolar and bronchiolar cells, including putative stem/progenitor cell populations. PMID:23204392

Archetypal analysis of diverse Pseudomonas aeruginosa transcriptomes reveals adaptation in cystic fibrosis airways

PubMed Central

2013-01-01

Background Analysis of global gene expression by DNA microarrays is widely used in experimental molecular biology. However, the complexity of such high-dimensional data sets makes it difficult to fully understand the underlying biological features present in the data. The aim of this study is to introduce a method for DNA microarray analysis that provides an intuitive interpretation of data through dimension reduction and pattern recognition. We present the first “Archetypal Analysis” of global gene expression. The analysis is based on microarray data from five integrated studies of Pseudomonas aeruginosa isolated from the airways of cystic fibrosis patients. Results Our analysis clustered samples into distinct groups with comprehensible characteristics since the archetypes representing the individual groups are closely related to samples present in the data set. Significant changes in gene expression between different groups identified adaptive changes of the bacteria residing in the cystic fibrosis lung. The analysis suggests a similar gene expression pattern between isolates with a high mutation rate (hypermutators) despite accumulation of different mutations for these isolates. This suggests positive selection in the cystic fibrosis lung environment, and changes in gene expression for these isolates are therefore most likely related to adaptation of the bacteria. Conclusions Archetypal analysis succeeded in identifying adaptive changes of P. aeruginosa. The combination of clustering and matrix factorization made it possible to reveal minor similarities among different groups of data, which other analytical methods failed to identify. We suggest that this analysis could be used to supplement current methods used to analyze DNA microarray data. PMID:24059747

Toxicogenomic analysis of N-nitrosomorpholine induced changes in rat liver: Comparison of genomic and proteomic responses and anchoring to histopathological parameters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oberemm, A., E-mail: axel.oberemm@bfr.bund.d; Ahr, H.-J.; Bannasch, P.

2009-12-01

A common animal model of chemical hepatocarcinogenesis was used to examine the utility of transcriptomic and proteomic data to identify early biomarkers related to chemically induced carcinogenesis. N-nitrosomorpholine, a frequently used genotoxic model carcinogen, was applied via drinking water at 120 mg/L to male Wistar rats for 7 weeks followed by an exposure-free period of 43 weeks. Seven specimens of each treatment group (untreated control and 120 mg/L N-nitrosomorpholine in drinking water) were sacrificed at nine time points during and after N-nitrosomorpholine treatment. Individual samples from the liver were prepared for histological and toxicogenomic analyses. For histological detection of preneoplasticmore » and neoplastic tissue areas, sections were stained using antibodies against the placental form of glutathione-S-transferase (GST-P). Gene and protein expression profiles of liver tissue homogenates were analyzed using RG-U34A Affymetrix rat gene chips and two-dimensional gel electrophoresis-based proteomics, respectively. In order to compare results obtained by histopathology, transcriptomics and proteomics, GST-P-stained liver sections were evaluated morphometrically, which revealed a parallel time course of the area fraction of preneoplastic lesions and gene plus protein expression patterns. On the transcriptional level, an increase of hepatic GST-P expression was detectable as early as 3 weeks after study onset. Comparing deregulated genes and proteins, eight species were identified which showed a corresponding expression profile on both expression levels. Functional analysis suggests that these genes and corresponding proteins may be useful as biomarkers of early hepatocarcinogenesis.« less

Modes of Cell Death Induced by Photodynamic Therapy Using Zinc Phthalocyanine in Lung Cancer Cells Grown as a Monolayer and Three-Dimensional Multicellular Spheroids.

PubMed

Manoto, Sello L; Houreld, Nicolette; Hodgkinson, Natasha; Abrahamse, Heidi

2017-05-16

Photodynamic therapy (PDT) involves interaction of a photosensitizer, light, and molecular oxygen which produces singlet oxygen and subsequent tumour eradication. The development of second generation photosensitizers, such as phthalocyanines, has improved this technology. Customary monolayer cell culture techniques are, unfortunately, too simple to replicate treatment effects in vivo. Multicellular tumour spheroids may provide a better alternative since they mimic aspects of the human tumour environment. This study aimed to profile 84 genes involved in apoptosis following treatment with PDT on lung cancer cells (A549) grown in a monolayer versus three-dimensional multicellular tumour spheroids (250 and 500 μm). Gene expression profiling was performed 24 h post irradiation (680 nm; 5 J/cm²) with zinc sulfophthalocyanine (ZnPcS mix ) to determine the genes involved in apoptotic cell death. In the monolayer cells, eight pro-apoptotic genes were upregulated, and two were downregulated. In the multicellular tumour spheroids (250 µm) there was upregulation of only 1 gene while there was downregulation of 56 genes. Apoptosis in the monolayer cultured cells was induced via both the intrinsic and extrinsic apoptotic pathways. However, in the multicellular tumour spheroids (250 and 500 µm) the apoptotic pathway that was followed was not conclusive.

A systems biology approach to defining regulatory mechanisms for cartilage and tendon cell phenotypes.

PubMed

Mueller, A J; Tew, S R; Vasieva, O; Clegg, P D; Canty-Laird, E G

2016-09-27

Phenotypic plasticity of adult somatic cells has provided emerging avenues for the development of regenerative therapeutics. In musculoskeletal biology the mechanistic regulatory networks of genes governing the phenotypic plasticity of cartilage and tendon cells has not been considered systematically. Additionally, a lack of strategies to effectively reproduce in vitro functional models of cartilage and tendon is retarding progress in this field. De- and redifferentiation represent phenotypic transitions that may contribute to loss of function in ageing musculoskeletal tissues. Applying a systems biology network analysis approach to global gene expression profiles derived from common in vitro culture systems (monolayer and three-dimensional cultures) this study demonstrates common regulatory mechanisms governing de- and redifferentiation transitions in cartilage and tendon cells. Furthermore, evidence of convergence of gene expression profiles during monolayer expansion of cartilage and tendon cells, and the expression of key developmental markers, challenges the physiological relevance of this culture system. The study also suggests that oxidative stress and PI3K signalling pathways are key modulators of in vitro phenotypes for cells of musculoskeletal origin.

Effect of Uniaxial Tensile Cyclic Loading Regimes on Matrix Organization and Tenogenic Differentiation of Adipose-Derived Stem Cells Encapsulated within 3D Collagen Scaffolds

PubMed Central

Stasuk, Alexander

2017-01-01

Adipose-derived mesenchymal stem cells have become a popular cell choice for tendon repair strategies due to their relative abundance, ease of isolation, and ability to differentiate into tenocytes. In this study, we investigated the solo effect of different uniaxial tensile strains and loading frequencies on the matrix directionality and tenogenic differentiation of adipose-derived stem cells encapsulated within three-dimensional collagen scaffolds. Samples loaded at 0%, 2%, 4%, and 6% strains and 0.1 Hz and 1 Hz frequencies for 2 hours/day over a 7-day period using a custom-built uniaxial tensile strain bioreactor were characterized in terms of matrix organization, cell viability, and musculoskeletal gene expression profiles. The results displayed that the collagen fibers of the loaded samples exhibited increased matrix directionality with an increase in strain values. Gene expression analyses demonstrated that ASC-encapsulated collagen scaffolds loaded at 2% strain and 0.1 Hz frequency showed significant increases in extracellular matrix genes and tenogenic differentiation markers. Importantly, no cross-differentiation potential to osteogenic, chondrogenic, and myogenic lineages was observed at 2% strain and 0.1 Hz frequency loading condition. Thus, 2% strain and 0.1 Hz frequency were identified as the appropriate mechanical loading regime to induce tenogenic differentiation of adipose-derived stem cells cultured in a three-dimensional environment. PMID:29375625

Collective Dynamics of Specific Gene Ensembles Crucial for Neutrophil Differentiation: The Existence of Genome Vehicles Revealed

PubMed Central

Giuliani, Alessandro; Tomita, Masaru

2010-01-01

Cell fate decision remarkably generates specific cell differentiation path among the multiple possibilities that can arise through the complex interplay of high-dimensional genome activities. The coordinated action of thousands of genes to switch cell fate decision has indicated the existence of stable attractors guiding the process. However, origins of the intracellular mechanisms that create “cellular attractor” still remain unknown. Here, we examined the collective behavior of genome-wide expressions for neutrophil differentiation through two different stimuli, dimethyl sulfoxide (DMSO) and all-trans-retinoic acid (atRA). To overcome the difficulties of dealing with single gene expression noises, we grouped genes into ensembles and analyzed their expression dynamics in correlation space defined by Pearson correlation and mutual information. The standard deviation of correlation distributions of gene ensembles reduces when the ensemble size is increased following the inverse square root law, for both ensembles chosen randomly from whole genome and ranked according to expression variances across time. Choosing the ensemble size of 200 genes, we show the two probability distributions of correlations of randomly selected genes for atRA and DMSO responses overlapped after 48 hours, defining the neutrophil attractor. Next, tracking the ranked ensembles' trajectories, we noticed that only certain, not all, fall into the attractor in a fractal-like manner. The removal of these genome elements from the whole genomes, for both atRA and DMSO responses, destroys the attractor providing evidence for the existence of specific genome elements (named “genome vehicle”) responsible for the neutrophil attractor. Notably, within the genome vehicles, genes with low or moderate expression changes, which are often considered noisy and insignificant, are essential components for the creation of the neutrophil attractor. Further investigations along with our findings might provide a comprehensive mechanistic view of cell fate decision. PMID:20725638

Microfluidic Device to Quantify the Behavior of Therapeutic Bacteria in Three-Dimensional Tumor Tissue.

PubMed

Brackett, Emily L; Swofford, Charles A; Forbes, Neil S

2016-01-01

Microfluidic devices enable precise quantification of the interactions between anti-cancer bacteria and tumor tissue. Direct observation of bacterial movement and gene expression in tissue is difficult with either monolayers of cells or tumor-bearing mice. Quantification of these interactions is necessary to understand the inherent mechanisms of bacterial targeting and to develop modified organisms with enhanced therapeutic properties. Here we describe the procedures for designing, printing, and assembling microfluidic tumor-on-a-chip devices. We also describe the procedures for inserting three-dimensional tumor-cell masses, exposure to bacteria, and analyzing the resultant images.

Joint principal trend analysis for longitudinal high-dimensional data.

PubMed

Zhang, Yuping; Ouyang, Zhengqing

2018-06-01

We consider a research scenario motivated by integrating multiple sources of information for better knowledge discovery in diverse dynamic biological processes. Given two longitudinal high-dimensional datasets for a group of subjects, we want to extract shared latent trends and identify relevant features. To solve this problem, we present a new statistical method named as joint principal trend analysis (JPTA). We demonstrate the utility of JPTA through simulations and applications to gene expression data of the mammalian cell cycle and longitudinal transcriptional profiling data in response to influenza viral infections. © 2017, The International Biometric Society.

Peripheral Blood Mononuclear Cells Enhance the Anabolic Effects of Platelet-Rich Plasma on Anterior Cruciate Ligament Fibroblasts

PubMed Central

Yoshida, Ryu; Murray, Martha M.

2012-01-01

Use of platelet-rich plasma (PRP) has shown promise in various orthopaedic applications, including treatment of anterior cruciate ligament (ACL) injuries. However, various components of blood, including peripheral blood mononuclear cells (PBMCs), are removed in the process of making PRP. It is yet unknown whether these PBMCs have a positive or negative effect on fibroblast behavior. To begin to define the effect of PBMCs on ACL fibroblasts, ACL fibroblasts were cultured on three-dimensional collagen scaffolds for 14 days with and without PBMCs. ACL fibroblasts exposed to PBMCs showed increased type I and type III procollagen gene expression, collagen protein expression, and cell proliferation when the cells were cultured in the presence of platelets and plasma. However, addition of PBMCs to cells cultured without the presence of platelets had no effect. The increase in collagen gene and protein expression was accompanied by an increase in IL-6 expression by the PBMCs with exposure to the platelets. Our results suggest that the interaction between platelets and PBMCs leads to an IL-6 mediated increase in collagen expression by ACL fibroblasts. PMID:22767425

Identifying cell and molecular stress after radiation in a three-dimensional (3-D) model of oral mucositis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lambros, Maria Polikandritou, E-mail: mlambros@westernu.edu; Parsa, Cyrus; Mulamalla, HariChandana

2011-02-04

Research highlights: {yields} We irradiated a 3-D human oral cell culture of keratinocytes and fibroblasts with 12 and 2 Gy. {yields} 6 h after irradiation the histopathology and apoptosis of the 3-D culture were evaluated. Microarrays were used to assess the gene expression in the irradiated 3-D tissue. {yields} 12 Gy induced significant histopathologic changes and cellular apoptosis. {yields} 12 Gy significantly affected genes of the NF-kB pathway, inflammatory cytokines and DAMPs. -- Abstract: Mucositis is a debilitating adverse effect of chemotherapy and radiation treatment. It is important to develop a simple and reliable in vitro model, which can routinelymore » be used to screen new drugs for prevention and treatment of mucositis. Furthermore, identifying cell and molecular stresses especially in the initiation phase of mucositis in this model will help towards this end. We evaluated a three-dimensional (3-D) human oral cell culture that consisted of oral keratinocytes and fibroblasts as a model of oral mucositis. The 3-D cell culture model was irradiated with 12 or 2 Gy. Six hours after the irradiation we evaluated microscopic sections of the cell culture for evidence of morphologic changes including apoptosis. We used microarrays to compare the expression of several genes from the irradiated tissue with identical genes from tissue that was not irradiated. We found that irradiation with 12 Gy induced significant histopathologic effects including cellular apoptosis. Irradiation significantly affected the expression of several genes of the NF-kB pathway and several inflammatory cytokines, such as IL-1B, 1L-8, NF-kB1, and FOS compared to tissue that was not irradiated. We identified significant upregulation of several genes that belong to damage-associated molecular patterns (DAMPs) such as HMB1, S100A13, SA10014, and SA10016 in the 3-D tissues that received 12 Gy but not in tissues that received 2 Gy. In conclusion, this model quantifies radiation damage and this is an important first step towards the development 3-D tissue as a screening tool.« less

Expression Profiles of the Trehalose-6-Phosphate Synthase Gene Associated With Thermal Stress in Ostrinia furnacalis (Lepidoptera: Crambidae)

PubMed Central

Jin, Tingting; Gao, Yulin; He, Kanglai

2018-01-01

Abstract Trehalose is the major blood sugar in insects. Physiological significance of this compound has been extensively reported. Trehalose-6-phosphate synthase (TPS) is an important enzyme in the trehalose biosynthesis pathway. Full-length cDNAs of TPS (Of tps) and its alternative splicing isoform (Of tps_isoformI) were cloned from the Asian corn borer (ACB), Ostrinia furnacalis (Guenée; Lepidoptera: Crambidae) larvae. The Of tps and Of tps_isoformI transcripts were 2913 and 1689 bp long, contained 2529 and 1293 bp open reading frames encoding proteins of 842 and 430 amino acids with a molecular mass of 94.4 and 48.6 kDa, respectively. Transcriptional profiling and response to thermal stress of Of tps gene were determined by quantitative real-time PCR showing that the Of tps was predominantly expressed in the larval fat body, significantly enhanced during molting and transformation; and thermal stress also induced Of tps expression. Gene structure analysis is indicating that one TPS domain and one trehalose-6-phosphate phosphatase (TPP) domain were located at the N- and C-termini of Of        TPS, respectively, while only the TPS domain was detected in OfTPS_isoformI. Three-dimensional modeling and heterologous expression were developed to predict the putative functions of OfTPS and Of   TPS_isoformI. We infer that the expression of Of tps gene is thermally induced and might be crucial for larvae survival.

Network-directed cis-mediator analysis of normal prostate tissue expression profiles reveals downstream regulatory associations of prostate cancer susceptibility loci.

PubMed

Larson, Nicholas B; McDonnell, Shannon K; Fogarty, Zach; Larson, Melissa C; Cheville, John; Riska, Shaun; Baheti, Saurabh; Weber, Alexandra M; Nair, Asha A; Wang, Liang; O'Brien, Daniel; Davila, Jaime; Schaid, Daniel J; Thibodeau, Stephen N

2017-10-17

Large-scale genome-wide association studies have identified multiple single-nucleotide polymorphisms associated with risk of prostate cancer. Many of these genetic variants are presumed to be regulatory in nature; however, follow-up expression quantitative trait loci (eQTL) association studies have to-date been restricted largely to cis -acting associations due to study limitations. While trans -eQTL scans suffer from high testing dimensionality, recent evidence indicates most trans -eQTL associations are mediated by cis -regulated genes, such as transcription factors. Leveraging a data-driven gene co-expression network, we conducted a comprehensive cis -mediator analysis using RNA-Seq data from 471 normal prostate tissue samples to identify downstream regulatory associations of previously identified prostate cancer risk variants. We discovered multiple trans -eQTL associations that were significantly mediated by cis -regulated transcripts, four of which involved risk locus 17q12, proximal transcription factor HNF1B , and target trans -genes with known HNF response elements ( MIA2 , SRC , SEMA6A , KIF12 ). We additionally identified evidence of cis -acting down-regulation of MSMB via rs10993994 corresponding to reduced co-expression of NDRG1 . The majority of these cis -mediator relationships demonstrated trans -eQTL replicability in 87 prostate tissue samples from the Gene-Tissue Expression Project. These findings provide further biological context to known risk loci and outline new hypotheses for investigation into the etiology of prostate cancer.

Branches of the NF-κB signaling pathway regulate proliferation of oval cells in rat liver regeneration.

PubMed

Zhao, W M; Qin, Y L; Niu, Z P; Chang, C F; Yang, J; Li, M H; Zhou, Y; Xu, C S

2016-03-24

The NF-kB (nuclear factor kB) pathway is involved in the proliferation of many cell types. To explore the mechanism of the NF-kB signaling pathway underlying the oval cell proliferation during rat liver regeneration, the Rat Genome 230 2.0 Array was used to detect expression changes of NF-kB signaling pathway-related genes in oval cells. The results revealed that the expression levels of many genes in the NF-kB pathway were significantly changed. This included 48 known genes and 16 homologous genes, as well as 370 genes and 85 homologous genes related to cell proliferation. To further understand the biological significance of these changes, an expression profile function was used to analyze the potential biological processes. The results showed that the NF-kB pathway promoted oval cell proliferation mainly through three signaling branches; the tumor necrosis factor alpha branch (TNF-a pathway), the growth factor branch, and the chemokine branch. An integrated statistics method was used to define the key genes in the NF-kB pathway. Seven genes were identified to play vital roles in the NF-kB pathway. To confirm these results, the protein content, including two key genes (TNF and FGF11) and two non-key genes (CCL2 and TNFRSF12A), were analyzed using two-dimensional gel electrophoresis and MALDI-TOF/TOF mass spectrometry. The results were generally consistent with those of the array data. To conclude, three branches and seven key genes were involved in the NF-kB signaling pathway that regulates oval cell proliferation during rat liver regeneration.

Three dimensional printing of calcium sulfate and mesoporous bioactive glass scaffolds for improving bone regeneration in vitro and in vivo

NASA Astrophysics Data System (ADS)

Qi, Xin; Pei, Peng; Zhu, Min; Du, Xiaoyu; Xin, Chen; Zhao, Shichang; Li, Xiaolin; Zhu, Yufang

2017-02-01

In the clinic, bone defects resulting from infections, trauma, surgical resection and genetic malformations remain a significant challenge. In the field of bone tissue engineering, three-dimensional (3D) scaffolds are promising for the treatment of bone defects. In this study, calcium sulfate hydrate (CSH)/mesoporous bioactive glass (MBG) scaffolds were successfully fabricated using a 3D printing technique, which had a regular and uniform square macroporous structure, high porosity and excellent apatite mineralization ability. Human bone marrow-derived mesenchymal stem cells (hBMSCs) were cultured on scaffolds to evaluate hBMSC attachment, proliferation and osteogenesis-related gene expression. Critical-sized rat calvarial defects were applied to investigate the effect of CSH/MBG scaffolds on bone regeneration in vivo. The in vitro results showed that CSH/MBG scaffolds stimulated the adhesion, proliferation, alkaline phosphatase (ALP) activity and osteogenesis-related gene expression of hBMSCs. In vivo results showed that CSH/MBG scaffolds could significantly enhance new bone formation in calvarial defects compared to CSH scaffolds. Thus 3D printed CSH/MBG scaffolds would be promising candidates for promoting bone regeneration.

Network-constrained group lasso for high-dimensional multinomial classification with application to cancer subtype prediction.

PubMed

Tian, Xinyu; Wang, Xuefeng; Chen, Jun

2014-01-01

Classic multinomial logit model, commonly used in multiclass regression problem, is restricted to few predictors and does not take into account the relationship among variables. It has limited use for genomic data, where the number of genomic features far exceeds the sample size. Genomic features such as gene expressions are usually related by an underlying biological network. Efficient use of the network information is important to improve classification performance as well as the biological interpretability. We proposed a multinomial logit model that is capable of addressing both the high dimensionality of predictors and the underlying network information. Group lasso was used to induce model sparsity, and a network-constraint was imposed to induce the smoothness of the coefficients with respect to the underlying network structure. To deal with the non-smoothness of the objective function in optimization, we developed a proximal gradient algorithm for efficient computation. The proposed model was compared to models with no prior structure information in both simulations and a problem of cancer subtype prediction with real TCGA (the cancer genome atlas) gene expression data. The network-constrained mode outperformed the traditional ones in both cases.

CellAtlasSearch: a scalable search engine for single cells.

PubMed

Srivastava, Divyanshu; Iyer, Arvind; Kumar, Vibhor; Sengupta, Debarka

2018-05-21

Owing to the advent of high throughput single cell transcriptomics, past few years have seen exponential growth in production of gene expression data. Recently efforts have been made by various research groups to homogenize and store single cell expression from a large number of studies. The true value of this ever increasing data deluge can be unlocked by making it searchable. To this end, we propose CellAtlasSearch, a novel search architecture for high dimensional expression data, which is massively parallel as well as light-weight, thus infinitely scalable. In CellAtlasSearch, we use a Graphical Processing Unit (GPU) friendly version of Locality Sensitive Hashing (LSH) for unmatched speedup in data processing and query. Currently, CellAtlasSearch features over 300 000 reference expression profiles including both bulk and single-cell data. It enables the user query individual single cell transcriptomes and finds matching samples from the database along with necessary meta information. CellAtlasSearch aims to assist researchers and clinicians in characterizing unannotated single cells. It also facilitates noise free, low dimensional representation of single-cell expression profiles by projecting them on a wide variety of reference samples. The web-server is accessible at: http://www.cellatlassearch.com.

Melanoma Spheroid Formation Involves Laminin-Associated Vasculogenic Mimicry

PubMed Central

Larson, Allison R.; Lee, Chung-Wei; Lezcano, Cecilia; Zhan, Qian; Huang, John; Fischer, Andrew H.; Murphy, George F.

2015-01-01

Melanoma is a tumor where virulence is conferred on transition from flat (radial) to three-dimensional (tumorigenic) growth. Virulence of tumorigenic growth is governed by numerous attributes, including presence of self-renewing stem-like cells and related formation of patterned networks associated with the melanoma mitogen, laminin, a phenomenon known as vasculogenic mimicry. Vasculogenic mimicry is posited to contribute to melanoma perfusion and nutrition in vivo; we hypothesized that it may also play a role in stem cell–driven spheroid formation in vitro. Using a model of melanoma in vitro tumorigenesis, laminin-associated networks developed in association with three-dimensional melanoma spheroids. Real-time PCR analysis of laminin subunits showed that spheroids formed from anchorage-independent melanoma cells expressed increased α4 and β1 laminin chains and α4 laminin expression was confirmed by in situ hybridization. Association of laminin networks with melanoma stem cell–associated nestin and vascular endothelial growth factor receptor-1 also was documented. Moreover, knockdown of nestin gene expression impaired laminin expression and network formation within spheroids. Laminin networks were remarkably similar to those observed in melanoma xenografts in mice and to those seen in patient melanomas. These data indicate that vasculogenic mimicry–like laminin networks, in addition to their genesis in vivo, are integral to the extracellular architecture of melanoma spheroids in vitro, where they may serve as stimulatory scaffolds to support three-dimensional growth. PMID:24332013

Human neural stem cell-derived cultures in three-dimensional substrates form spontaneously functional neuronal networks.

PubMed

Smith, Imogen; Silveirinha, Vasco; Stein, Jason L; de la Torre-Ubieta, Luis; Farrimond, Jonathan A; Williamson, Elizabeth M; Whalley, Benjamin J

2017-04-01

Differentiated human neural stem cells were cultured in an inert three-dimensional (3D) scaffold and, unlike two-dimensional (2D) but otherwise comparable monolayer cultures, formed spontaneously active, functional neuronal networks that responded reproducibly and predictably to conventional pharmacological treatments to reveal functional, glutamatergic synapses. Immunocytochemical and electron microscopy analysis revealed a neuronal and glial population, where markers of neuronal maturity were observed in the former. Oligonucleotide microarray analysis revealed substantial differences in gene expression conferred by culturing in a 3D vs a 2D environment. Notable and numerous differences were seen in genes coding for neuronal function, the extracellular matrix and cytoskeleton. In addition to producing functional networks, differentiated human neural stem cells grown in inert scaffolds offer several significant advantages over conventional 2D monolayers. These advantages include cost savings and improved physiological relevance, which make them better suited for use in the pharmacological and toxicological assays required for development of stem cell-based treatments and the reduction of animal use in medical research. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

GAC: Gene Associations with Clinical, a web based application

PubMed Central

Zhang, Xinyan; Rupji, Manali; Kowalski, Jeanne

2018-01-01

We present GAC, a shiny R based tool for interactive visualization of clinical associations based on high-dimensional data. The tool provides a web-based suite to perform supervised principal component analysis (SuperPC), an approach that uses both high-dimensional data, such as gene expression, combined with clinical data to infer clinical associations. We extended the approach to address binary outcomes, in addition to continuous and time-to-event data in our package, thereby increasing the use and flexibility of SuperPC.  Additionally, the tool provides an interactive visualization for summarizing results based on a forest plot for both binary and time-to-event data.  In summary, the GAC suite of tools provide a one stop shop for conducting statistical analysis to identify and visualize the association between a clinical outcome of interest and high-dimensional data types, such as genomic data. Our GAC package has been implemented in R and is available via http://shinygispa.winship.emory.edu/GAC/. The developmental repository is available at https://github.com/manalirupji/GAC. PMID:29263780

Isolation, characterization and expression analysis of the BABY BOOM (BBM) gene from Larix kaempferi × L. olgensis during adventitious rooting.

PubMed

Li, Kui-Peng; Sun, Xiao-Mei; Han, Hua; Zhang, Shou-Gong

2014-11-10

The full-length cDNA and genomic sequences of the BABY BOOM (BBM) gene, designated LkBBM, were isolated from Larix kaempferi × Larix olgensis. The 3324 bp cDNA was cloned and its open reading frame (ORF) consists of 2370 nucleotides. The deduced 789 amino acid protein contains two AP2 domains and a BBM specific motif. Four conserved motifs between BBM and PLT were identified, which may be conducive to the similar function of BBM and PLT. The three dimensional (3D) structure of LkBBM was predicted and β-sheets in the AP2-R2 domain of LkBBM might recognize the specific base pairs in the major groove. Analysis of the LkBBM gene structure indicates that the gene has eight introns and nine exons. In the 5'-flanking promoter region of LkBBM, many important potential cis-acting elements were identified, such as the TATABOX5 element (a functional TATA element), ROOTMOTIFTAPOX1 element (element of root specificity), AUXREPSIAA4 element (element involved in auxin responsiveness and gene expression in root meristem), MYB1AT element (element involved in MYB recognition), ARR1AT element (element involved in cytokinin responsiveness), GARE1OSREP1 element (element involved in gibberellin responsiveness) and PYRIMIDINEBOXHVEPB1 element (element involved in abscisic acid responsiveness), which all suggested that the expression of LkBBM is highly regulated. Compared with gene expression levels in the stem, stem tip and leaf, LkBBM shows a specific expression in the root, which indicates that LkBBM plays a key role in regulating the development and growth of root in larch. In the processing of larch adventitious root formation, LkBBM started to express on the eighth day after rooting treatment and its transcript level increased continuously afterwards. According to the gene characteristics, LkBBM is proposed as a molecular marker for root primordia of larch, and the initial period of LkBBM expression may be the formation period of root primordia in the processing of adventitious rooting of larch. Copyright © 2014 Elsevier B.V. All rights reserved.

Analysis of the GRNs Inference by Using Tsallis Entropy and a Feature Selection Approach

NASA Astrophysics Data System (ADS)

Lopes, Fabrício M.; de Oliveira, Evaldo A.; Cesar, Roberto M.

An important problem in the bioinformatics field is to understand how genes are regulated and interact through gene networks. This knowledge can be helpful for many applications, such as disease treatment design and drugs creation purposes. For this reason, it is very important to uncover the functional relationship among genes and then to construct the gene regulatory network (GRN) from temporal expression data. However, this task usually involves data with a large number of variables and small number of observations. In this way, there is a strong motivation to use pattern recognition and dimensionality reduction approaches. In particular, feature selection is specially important in order to select the most important predictor genes that can explain some phenomena associated with the target genes. This work presents a first study about the sensibility of entropy methods regarding the entropy functional form, applied to the problem of topology recovery of GRNs. The generalized entropy proposed by Tsallis is used to study this sensibility. The inference process is based on a feature selection approach, which is applied to simulated temporal expression data generated by an artificial gene network (AGN) model. The inferred GRNs are validated in terms of global network measures. Some interesting conclusions can be drawn from the experimental results, as reported for the first time in the present paper.

Learning a single-hidden layer feedforward neural network using a rank correlation-based strategy with application to high dimensional gene expression and proteomic spectra datasets in cancer detection.

PubMed

Belciug, Smaranda; Gorunescu, Florin

2018-06-08

Methods based on microarrays (MA), mass spectrometry (MS), and machine learning (ML) algorithms have evolved rapidly in recent years, allowing for early detection of several types of cancer. A pitfall of these approaches, however, is the overfitting of data due to large number of attributes and small number of instances -- a phenomenon known as the 'curse of dimensionality'. A potentially fruitful idea to avoid this drawback is to develop algorithms that combine fast computation with a filtering module for the attributes. The goal of this paper is to propose a statistical strategy to initiate the hidden nodes of a single-hidden layer feedforward neural network (SLFN) by using both the knowledge embedded in data and a filtering mechanism for attribute relevance. In order to attest its feasibility, the proposed model has been tested on five publicly available high-dimensional datasets: breast, lung, colon, and ovarian cancer regarding gene expression and proteomic spectra provided by cDNA arrays, DNA microarray, and MS. The novel algorithm, called adaptive SLFN (aSLFN), has been compared with four major classification algorithms: traditional ELM, radial basis function network (RBF), single-hidden layer feedforward neural network trained by backpropagation algorithm (BP-SLFN), and support vector-machine (SVM). Experimental results showed that the classification performance of aSLFN is competitive with the comparison models. Copyright © 2018. Published by Elsevier Inc.

Perturbation of nuclear architecture by long-distance chromosome interactions.

PubMed

Dernburg, A F; Broman, K W; Fung, J C; Marshall, W F; Philips, J; Agard, D A; Sedat, J W

1996-05-31

Position-effect variegation (PEV) describes the stochastic transcriptional silencing of a gene positioned adjacent to heterochromatin. Using FISH, we have tested whether variegated expression of the eye-color gene brown in Drosophila is influenced by its nuclear localization. In embryonic nuclei, a heterochromatic insertion at the brown locus is always spatially isolated from other heterochromatin. However, during larval development this insertion physically associates with other heterochromatic regions on the same chromosome in a stochastic manner. These observations indicate that the brown gene is silenced by specific contact with centromeric heterochromatin. Moreover, they provide direct evidence for long-range chromosome interactions and their impact on three-dimensional nuclear architecture, while providing a cohesive explanation for the phenomenon of PEV.

Serum- and Growth-Factor-Free Three-Dimensional Culture System Supports Cartilage Tissue Formation by Promoting Collagen Synthesis via Sox9–Col2a1 Interaction

PubMed Central

Ahmed, Nazish; Iu, Jonathan; Brown, Chelsea E.; Taylor, Drew Wesley

2014-01-01

Objective: One of the factors preventing clinical application of regenerative medicine to degenerative cartilage diseases is a suitable source of cells. Chondrocytes, the only cell type of cartilage, grown in vitro under culture conditions to expand cell numbers lose their phenotype along with the ability to generate hyaline cartilaginous tissue. In this study we determine that a serum- and growth-factor-free three-dimensional (3D) culture system restores the ability of the passaged chondrocytes to form cartilage tissue in vitro, a process that involves sox9. Methods: Bovine articular chondrocytes were passaged twice to allow for cell number expansion (P2) and cultured at high density on 3D collagen-type-II-coated membranes in high glucose content media supplemented with insulin and dexamethasone (SF3D). The cells were characterized after monolayer expansion and following 3D culture by flow cytometry, gene expression, and histology. The early changes in signaling transduction pathways during redifferentiation were characterized. Results: The P2 cells showed a progenitor-like antigen profile of 99% CD44+ and 40% CD105+ and a gene expression profile suggestive of interzone cells. P2 in SF3D expressed chondrogenic genes and accumulated extracellular matrix. Downregulating insulin receptor (IR) with HNMPA-(AM3) or the PI-3/AKT kinase pathway (activated by insulin treatment) with Wortmannin inhibited collagen synthesis. HNMPA-(AM3) reduced expression of Col2, Col11, and IR genes as well as Sox6 and -9. Co-immunoprecipitation and chromatin immunoprecipitation analyses of HNMPA-(AM3)-treated cells showed binding of the coactivators Sox6 and Med12 with Sox9 but reduced Sox9–Col2a1 binding. Conclusions: We describe a novel culture method that allows for increase in the number of chondrocytes and promotes hyaline-like cartilage tissue formation in part by insulin-mediated Sox9–Col2a1 binding. The suitability of the tissue generated via this approach for use in joint repair needs to be examined in vivo. PMID:24606204

Evaluation of STAT5A Gene Expression in Aflatoxin B1 Treated Bovine Mammary Epithelial Cells

PubMed Central

Forouharmehr, Ali; Harkinezhad, Taher; Qasemi-Panahi, Babak

2013-01-01

Purpose: Aflatoxin B1 (AFB1) is a potent mycotoxin which has been produced by fungi such as Aspergillus flavus and Aspergillus parasiticus as secondary metabolites due to their growth on food stuffs and induces hepatocellular carcinoma in many animal species, including humans. In the present study, the effect of AFB1 on STAT5A gene expression was investigated in bovine mammary epithelial cells using real time RT-PCR. Methods: Bovine mammary epithelial cells were seeded in a 24-well culture plate for three-dimensional (3D) culture in Matrigel matrix. After 21 days of 3D culture and reaching the required number of cells, cells were treated with AFB1 and incubated for 8 h. For real time PCR reaction, total RNA from the cultured and treated cells was extracted and used for complementary DNA synthesis. Results: The expression of STAT5A gene was significantly down regulated by AFB1 in dose- dependent manner and led to the reduction of proliferation and differentiation of epithelial cells, which has direct effect in milk protein quantity and quality. Conclusion: According to the results, it seems that down regulation of STAT5A gene in AFB1-treated cells maybe due to DNA damage induced by AFB1 in bovine mammary epithelial cells. PMID:24312879

Characterizing the Grape Transcriptome. Analysis of Expressed Sequence Tags from Multiple Vitis Species and Development of a Compendium of Gene Expression during Berry Development1[w

PubMed Central

Silva, Francisco Goes da; Iandolino, Alberto; Al-Kayal, Fadi; Bohlmann, Marlene C.; Cushman, Mary Ann; Lim, Hyunju; Ergul, Ali; Figueroa, Rubi; Kabuloglu, Elif K.; Osborne, Craig; Rowe, Joan; Tattersall, Elizabeth; Leslie, Anna; Xu, Jane; Baek, JongMin; Cramer, Grant R.; Cushman, John C.; Cook, Douglas R.

2005-01-01

We report the analysis and annotation of 146,075 expressed sequence tags from Vitis species. The majority of these sequences were derived from different cultivars of Vitis vinifera, comprising an estimated 25,746 unique contig and singleton sequences that survey transcription in various tissues and developmental stages and during biotic and abiotic stress. Putatively homologous proteins were identified for over 17,752 of the transcripts, with 1,962 transcripts further subdivided into one or more Gene Ontology categories. A simple structured vocabulary, with modules for plant genotype, plant development, and stress, was developed to describe the relationship between individual expressed sequence tags and cDNA libraries; the resulting vocabulary provides query terms to facilitate data mining within the context of a relational database. As a measure of the extent to which characterized metabolic pathways were encompassed by the data set, we searched for homologs of the enzymes leading from glycolysis, through the oxidative/nonoxidative pentose phosphate pathway, and into the general phenylpropanoid pathway. Homologs were identified for 65 of these 77 enzymes, with 86% of enzymatic steps represented by paralogous genes. Differentially expressed transcripts were identified by means of a stringent believability index cutoff of ≥98.4%. Correlation analysis and two-dimensional hierarchical clustering grouped these transcripts according to similarity of expression. In the broadest analysis, 665 differentially expressed transcripts were identified across 29 cDNA libraries, representing a range of developmental and stress conditions. The groupings revealed expected associations between plant developmental stages and tissue types, with the notable exception of abiotic stress treatments. A more focused analysis of flower and berry development identified 87 differentially expressed transcripts and provides the basis for a compendium that relates gene expression and annotation to previously characterized aspects of berry development and physiology. Comparison with published results for select genes, as well as correlation analysis between independent data sets, suggests that the inferred in silico patterns of expression are likely to be an accurate representation of transcript abundance for the conditions surveyed. Thus, the combined data set reveals the in silico expression patterns for hundreds of genes in V. vinifera, the majority of which have not been previously studied within this species. PMID:16219919

Leptin expression in mandarin fish Siniperca chuatsi (Basilewsky): Regulation by postprandial and short-term fasting treatment.

PubMed

Yuan, Xiaochen; Li, Aixuan; Liang, Xu-Fang; Huang, Wei; Song, Yi; He, Shan; Cai, Wenjing; Tao, Ya-xiong

2016-04-01

Most fish species possess duplicate leptin genes (LEP). Mandarin fish (Siniperca chuatsi) leptin A gene (sLEP-A) have been cloned in the previous study. In the present study, we cloned and characterized leptin B gene (sLEP-B) in mandarin fish, including a 471bp open reading frame (ORF) encoding a 158-amino acid protein. The three-dimensional (3D) structural model of sLEP-B protein showed a highly conserved of tertiary structure similar to that of other vertebrates. Genomic sequencing results indicated that sLEP-B possessed only one intron. This is the first report of the loss of an intron in LEP-B in Perciformes. The different distribution patterns of sLEPs suggest different physiological roles of these two genes. The presence of HNF3β, a liver-enriched transcription factor, only in sLEP-A indicated abundant expression and metabolic function of sLEP-A in the liver. In an in vivo experiment, the expressions of brain sLEP-A and sLEP-B were observed to increase after a meal. During the short-term fasting, the expressions of sLEPs in mandarin fish brain were decreased significantly. A persistent and significant increase in hepatic sLEP-A expression supported a relationship between leptin and food intake in mandarin fish. These results suggest that sLEP-A plays an important role in the regulation of energy homeostasis in this carnivorous fish, and sLEP-B is probably a specialized gene responsible for the central nervous system (CNS) control of energy regulation. Copyright © 2016 Elsevier Inc. All rights reserved.

A Unique Procedure to Identify Cell Surface Markers Through a Spherical Self-Organizing Map Applied to DNA Microarray Analysis.

PubMed

Sugii, Yuh; Kasai, Tomonari; Ikeda, Masashi; Vaidyanath, Arun; Kumon, Kazuki; Mizutani, Akifumi; Seno, Akimasa; Tokutaka, Heizo; Kudoh, Takayuki; Seno, Masaharu

2016-01-01

To identify cell-specific markers, we designed a DNA microarray platform with oligonucleotide probes for human membrane-anchored proteins. Human glioma cell lines were analyzed using microarray and compared with normal and fetal brain tissues. For the microarray analysis, we employed a spherical self-organizing map, which is a clustering method suitable for the conversion of multidimensional data into two-dimensional data and displays the relationship on a spherical surface. Based on the gene expression profile, the cell surface characteristics were successfully mirrored onto the spherical surface, thereby distinguishing normal brain tissue from the disease model based on the strength of gene expression. The clustered glioma-specific genes were further analyzed by polymerase chain reaction procedure and immunocytochemical staining of glioma cells. Our platform and the following procedure were successfully demonstrated to categorize the genes coding for cell surface proteins that are specific to glioma cells. Our assessment demonstrates that a spherical self-organizing map is a valuable tool for distinguishing cell surface markers and can be employed in marker discovery studies for the treatment of cancer.

OVCAR-3 Spheroid-Derived Cells Display Distinct Metabolic Profiles

PubMed Central

Vermeersch, Kathleen A.; Wang, Lijuan; Mezencev, Roman; McDonald, John F.; Styczynski, Mark P.

2015-01-01

Introduction Recently, multicellular spheroids were isolated from a well-established epithelial ovarian cancer cell line, OVCAR-3, and were propagated in vitro. These spheroid-derived cells displayed numerous hallmarks of cancer stem cells, which are chemo- and radioresistant cells thought to be a significant cause of cancer recurrence and resultant mortality. Gene set enrichment analysis of expression data from the OVCAR-3 cells and the spheroid-derived putative cancer stem cells identified several metabolic pathways enriched in differentially expressed genes. Before this, there had been little previous knowledge or investigation of systems-scale metabolic differences between cancer cells and cancer stem cells, and no knowledge of such differences in ovarian cancer stem cells. Methods To determine if there were substantial metabolic changes corresponding with these transcriptional differences, we used two-dimensional gas chromatography coupled to mass spectrometry to measure the metabolite profiles of the two cell lines. Results These two cell lines exhibited significant metabolic differences in both intracellular and extracellular metabolite measurements. Principal components analysis, an unsupervised dimensional reduction technique, showed complete separation between the two cell types based on their metabolite profiles. Pathway analysis of intracellular metabolomics data revealed close overlap with metabolic pathways identified from gene expression data, with four out of six pathways found enriched in gene-level analysis also enriched in metabolite-level analysis. Some of those pathways contained multiple metabolites that were individually statistically significantly different between the two cell lines, with one of the most broadly and consistently different pathways, arginine and proline metabolism, suggesting an interesting hypothesis about cancerous and stem-like metabolic phenotypes in this pair of cell lines. Conclusions Overall, we demonstrate for the first time that metabolism in an ovarian cancer stem cell line is distinct from that of more differentiated isogenic cancer cells, supporting the potential importance of metabolism in the differences between cancer cells and cancer stem cells. PMID:25688563

Molecular profiles of Quadriceps muscle in myostatin-null mice reveal PI3K and apoptotic pathways as myostatin targets

PubMed Central

Chelh, Ilham; Meunier, Bruno; Picard, Brigitte; Reecy, Mark James; Chevalier, Catherine; Hocquette, Jean-François; Cassar-Malek, Isabelle

2009-01-01

Background Myostatin (MSTN), a member of the TGF-β superfamily, has been identified as a negative regulator of skeletal muscle mass. Inactivating mutations in the MSTN gene are responsible for the development of a hypermuscular phenotype. In this study, we performed transcriptomic and proteomic analyses to detect altered expression/abundance of genes and proteins. These differentially expressed genes and proteins may represent new molecular targets of MSTN and could be involved in the regulation of skeletal muscle mass. Results Transcriptomic analysis of the Quadriceps muscles of 5-week-old MSTN-null mice (n = 4) and their controls (n = 4) was carried out using microarray (human and murine oligonucleotide sequences) of 6,473 genes expressed in muscle. Proteomic profiles were analysed using two-dimensional gel electrophoresis coupled with mass spectrometry. Comparison of the transcriptomic profiles revealed 192 up- and 245 down- regulated genes. Genes involved in the PI3K pathway, insulin/IGF pathway, carbohydrate metabolism and apoptosis regulation were up-regulated. Genes belonging to canonical Wnt, calcium signalling pathways and cytokine-receptor cytokine interaction were down-regulated. Comparison of the protein profiles revealed 20 up- and 18 down-regulated proteins spots. Knockout of the MSTN gene was associated with up-regulation of proteins involved in glycolytic shift of the muscles and down-regulation of proteins involved in oxidative energy metabolism. In addition, an increased abundance of survival/anti-apoptotic factors were observed. Conclusion All together, these results showed a differential expression of genes and proteins related to the muscle energy metabolism and cell survival/anti-apoptotic pathway (e.g. DJ-1, PINK1, 14-3-3ε protein, TCTP/GSK-3β). They revealed the PI3K and apoptotic pathways as MSTN targets and are in favour of a role of MSTN as a modulator of cell survival in vivo. PMID:19397818

Deciphering defective amelogenesis using in vitro culture systems.

PubMed

Arinawati, Dian Yosi; Miyoshi, Keiko; Tanimura, Ayako; Horiguchi, Taigo; Hagita, Hiroko; Noma, Takafumi

2018-04-01

The conventional two-dimensional (2D) in vitro culture system is frequently used to analyze the gene expression with or without extracellular signals. However, the cells derived from primary culture and cell lines frequently deviate the gene expression profile compared to the corresponding in vivo samples, which sometimes misleads the actual gene regulation in vivo. To overcome this gap, we developed the comparative 2D and 3D in vitro culture systems and applied them to the genetic study of amelogenesis imperfecta (AI) as a model. Recently, we found specificity protein 6 (Sp6) mutation in an autosomal-recessive AI rat that was previously named AMI. We constructed 3D structure of ARE-B30 cells (AMI-derived rat dental epithelial cells) or G5 (control wild type cells) combined with RPC-C2A cells (rat pulp cell line) separated by the collagen membrane, while in 2D structure, ARE-B30 or G5 was cultured with or without the collagen membrane. Comparative analysis of amelogenesis-related gene expression in ARE-B30 and G5 using our 2D and 3D in vitro systems revealed distinct expression profiles, showing the causative outcomes. Bone morphogenetic protein 2 and follistatin were reciprocally expressed in G5, but not in ARE-B30 cells. All-or-none expression of amelotin, kallikrein-related peptidase 4, and nerve growth factor receptor was observed in both cell types. In conclusion, our in vitro culture systems detected the phenotypical differences in the expression of the stage-specific amelogenesis-related genes. Parallel analysis with 2D and 3D culture systems may provide a platform to understand the molecular basis for defective amelogenesis caused by Sp6 mutation. Copyright © 2017 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Multiple mechanisms underlie defective recognition of melanoma cells cultured in three-dimensional architectures by antigen-specific cytotoxic T lymphocytes

PubMed Central

Feder-Mengus, C; Ghosh, S; Weber, W P; Wyler, S; Zajac, P; Terracciano, L; Oertli, D; Heberer, M; Martin, I; Spagnoli, G C; Reschner, A

2007-01-01

Cancer cells' growth in three-dimensional (3D) architectures promotes resistance to drugs, cytokines, or irradiation. We investigated effects of 3D culture as compared to monolayers (2D) on melanoma cells' recognition by tumour-associated antigen (TAA)-specific HLA-A*0201-restricted cytotoxic T-lymphocytes (CTL). Culture of HBL, D10 (both HLA-A*0201+, TAA+) and NA8 (HLA-A*0201+, TAA−) melanoma cells on polyHEMA-coated plates, resulted in generation of 3D multicellular tumour spheroids (MCTS). Interferon-gamma (IFN-γ) production by HLA-A*0201-restricted Melan-A/MART-127–35 or gp100280–288-specific CTL clones served as immunorecognition marker. Co-culture with melanoma MCTS, resulted in defective TAA recognition by CTL as compared to 2D as witnessed by decreased IFN-γ production and decreased Fas Ligand, perforin and granzyme B gene expression. A multiplicity of mechanisms were potentially involved. First, MCTS per se limit CTL capacity of recognising HLA class I restricted antigens by reducing exposed cell surfaces. Second, expression of melanoma differentiation antigens is downregulated in MCTS. Third, expression of HLA class I molecules can be downregulated in melanoma MCTS, possibly due to decreased interferon-regulating factor-1 gene expression. Fourth, lactic acid production is increased in MCTS, as compared to 2D. These data suggest that melanoma cells growing in 3D, even in the absence of immune selection, feature characteristics capable of dramatically inhibiting TAA recognition by specific CTL. PMID:17342088

MSL: A Measure to Evaluate Three-dimensional Patterns in Gene Expression Data

PubMed Central

Gutiérrez-Avilés, David; Rubio-Escudero, Cristina

2015-01-01

Microarray technology is highly used in biological research environments due to its ability to monitor the RNA concentration levels. The analysis of the data generated represents a computational challenge due to the characteristics of these data. Clustering techniques are widely applied to create groups of genes that exhibit a similar behavior. Biclustering relaxes the constraints for grouping, allowing genes to be evaluated only under a subset of the conditions. Triclustering appears for the analysis of longitudinal experiments in which the genes are evaluated under certain conditions at several time points. These triclusters provide hidden information in the form of behavior patterns from temporal experiments with microarrays relating subsets of genes, experimental conditions, and time points. We present an evaluation measure for triclusters called Multi Slope Measure, based on the similarity among the angles of the slopes formed by each profile formed by the genes, conditions, and times of the tricluster. PMID:26124630

Expression of transcription factors after short-term exposure of Arabidopsis thaliana cell cultures to hypergravity and simulated microgravity (2-D/3-D clinorotation, magnetic levitation)

NASA Astrophysics Data System (ADS)

Babbick, M.; Dijkstra, C.; Larkin, O. J.; Anthony, P.; Davey, M. R.; Power, J. B.; Lowe, K. C.; Cogoli-Greuter, M.; Hampp, R.

Gravity is an important environmental factor that controls plant growth and development. Studies have shown that the perception of gravity is not only a property of specialized cells, but can also be performed by undifferentiated cultured cells. In this investigation, callus of Arabidopsis thaliana cv. Columbia was used to investigate the initial steps of gravity-related signalling cascades, through altered expression of transcription factors (TFs). TFs are families of small proteins that regulate gene expression by binding to specific promoter sequences. Based on microarray studies, members of the gene families WRKY, MADS-box, MYB, and AP2/EREBP were selected for investigation, as well as members of signalling chains, namely IAA 19 and phosphoinositol-4-kinase. Using qRT-PCR, transcripts were quantified within a period of 30 min in response to hypergravity (8 g), clinorotation [2-D clinostat and 3-D random positioning machine (RPM)] and magnetic levitation (ML). The data indicated that (1) changes in gravity induced stress-related signalling, and (2) exposure in the RPM induced changes in gene expression which resemble those of magnetic levitation. Two dimensional clinorotation resulted in responses similar to those caused by hypergravity. It is suggested that RPM and ML are preferable to simulate microgravity than clinorotation.

High-Dimensional Sparse Factor Modeling: Applications in Gene Expression Genomics

PubMed Central

Carvalho, Carlos M.; Chang, Jeffrey; Lucas, Joseph E.; Nevins, Joseph R.; Wang, Quanli; West, Mike

2010-01-01

We describe studies in molecular profiling and biological pathway analysis that use sparse latent factor and regression models for microarray gene expression data. We discuss breast cancer applications and key aspects of the modeling and computational methodology. Our case studies aim to investigate and characterize heterogeneity of structure related to specific oncogenic pathways, as well as links between aggregate patterns in gene expression profiles and clinical biomarkers. Based on the metaphor of statistically derived “factors” as representing biological “subpathway” structure, we explore the decomposition of fitted sparse factor models into pathway subcomponents and investigate how these components overlay multiple aspects of known biological activity. Our methodology is based on sparsity modeling of multivariate regression, ANOVA, and latent factor models, as well as a class of models that combines all components. Hierarchical sparsity priors address questions of dimension reduction and multiple comparisons, as well as scalability of the methodology. The models include practically relevant non-Gaussian/nonparametric components for latent structure, underlying often quite complex non-Gaussianity in multivariate expression patterns. Model search and fitting are addressed through stochastic simulation and evolutionary stochastic search methods that are exemplified in the oncogenic pathway studies. Supplementary supporting material provides more details of the applications, as well as examples of the use of freely available software tools for implementing the methodology. PMID:21218139

Isolation, expression and characterization of rbcL gene from Ulva prolifera J. Agardh (Ulvophyceae, Chlorophyta)

NASA Astrophysics Data System (ADS)

Shao, Zhanru; Li, Wei; Guo, Hui; Duan, Delin

2015-12-01

Ulva prolifera is a typical green alga in subtidal areas and can grow tremendously fast. A highly efficient Rubisco enzyme which is encoded by UpRbcL gene may contribute to the rapid growth. In this study, the full-length UpRbcL open reading frame (ORF) was identified, which encoded a protein of 474 amino acids. Phylogenetic analysis of UpRbcL sequences revealed that Chlorophyta had a closer genetic relationship with higher plants than with Rhodophyta and Phaeophyta. The two distinct residues (aa11 and aa91) were presumed to be unique for Rubisco catalytic activity. The predicted three-dimensional structure showed that one α/β-barrel existed in the C-terminal region, and the sites for Mg2+ coordination and CO2 fixation were also located in this region. Gene expression profile indicated that UpRbcL was expressed at a higher level under light exposure than in darkness. When the culture temperature reached 35°C, the expression level of UpRbcL was 2.5-fold lower than at 15°C, and the carboxylase activity exhibited 13.8-fold decrease. UpRbcL was heterologously expressed in E. coli and was purified by Ni2+ affinity chromatography. The physiological and biochemical characterization of recombinant Rubisco will be explored in the future.

Titrated extract of Centella asiatica increases hair inductive property through inhibition of STAT signaling pathway in three-dimensional spheroid cultured human dermal papilla cells.

PubMed

Choi, Yeong Min; An, Sungkwan; Lee, Junwoo; Lee, Jae Ho; Lee, Jae Nam; Kim, Young Sam; Ahn, Kyu Joong; An, In-Sook; Bae, Seunghee

2017-12-01

Dermal papilla (DP) is a pivotal part of hair follicle, and the smaller size of the DP is related with the hair loss. In this study, we investigated the effect of titrated extract of Centella asiatica (TECA) on hair growth inductive property on 3D spheroid cultured human DP cells (HDP cells). Significantly increased effect of TECA on cell viability was only shown in 3D sphered HPD cells, not in 2D cultured HDP cells. Also, TECA treatment increased the sphere size of HDP cells. The luciferase activity of STAT reporter genes and the expression of STAT-targeted genes, SOCS1 and SOCS3, were significantly decreased. Also, TECA treatment increased the expression of the hair growth-related signature genes in 3D sphered HDP cells. Furthermore, TECA led to downregulation of the level of phosphorylated STAT proteins in 3D sphered HDP cells. Overall, TECA activates the potential of hair inductive capacity in HDP cells.

Three-dimensional cell culture models for investigating human viruses.

PubMed

He, Bing; Chen, Guomin; Zeng, Yi

2016-10-01

Three-dimensional (3D) culture models are physiologically relevant, as they provide reproducible results, experimental flexibility and can be adapted for high-throughput experiments. Moreover, these models bridge the gap between traditional two-dimensional (2D) monolayer cultures and animal models. 3D culture systems have significantly advanced basic cell science and tissue engineering, especially in the fields of cell biology and physiology, stem cell research, regenerative medicine, cancer research, drug discovery, and gene and protein expression studies. In addition, 3D models can provide unique insight into bacteriology, virology, parasitology and host-pathogen interactions. This review summarizes and analyzes recent progress in human virological research with 3D cell culture models. We discuss viral growth, replication, proliferation, infection, virus-host interactions and antiviral drugs in 3D culture models.

Interpretable dimensionality reduction of single cell transcriptome data with deep generative models.

PubMed

Ding, Jiarui; Condon, Anne; Shah, Sohrab P

2018-05-21

Single-cell RNA-sequencing has great potential to discover cell types, identify cell states, trace development lineages, and reconstruct the spatial organization of cells. However, dimension reduction to interpret structure in single-cell sequencing data remains a challenge. Existing algorithms are either not able to uncover the clustering structures in the data or lose global information such as groups of clusters that are close to each other. We present a robust statistical model, scvis, to capture and visualize the low-dimensional structures in single-cell gene expression data. Simulation results demonstrate that low-dimensional representations learned by scvis preserve both the local and global neighbor structures in the data. In addition, scvis is robust to the number of data points and learns a probabilistic parametric mapping function to add new data points to an existing embedding. We then use scvis to analyze four single-cell RNA-sequencing datasets, exemplifying interpretable two-dimensional representations of the high-dimensional single-cell RNA-sequencing data.

Three-dimensional image analysis of plugging at the septal pore by Woronin body during hypotonic shock inducing hyphal tip bursting in the filamentous fungus Aspergillus oryzae

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maruyama, Jun-ichi; Juvvadi, Praveen Rao; Ishi, Kazutomo

2005-06-17

We observed that the filamentous fungus, Aspergillus oryzae, grown on agar media burst out cytoplasmic constituents from the hyphal tip soon after flooding with water. Woronin body is a specialized organelle known to plug the septal pore adjacent to the lysed compartment to prevent extensive loss of cytoplasm. A. oryzae Aohex1 gene homologous to Neurospora crassa HEX1 gene encoding a major protein in Woronin body was expressed as a fusion with DsRed2, resulting in visualization of Woronin body. Confocal microscopy and three-dimensional reconstruction of images visualized the septal pore as a dark region surrounded by green fluorescence of EGFP-fused secretorymore » protein, RNase T1, on the septum. Dual fluorescent labeling revealed the plugging of the septal pores adjacent to the lysed apical compartments by Woronin bodies during hypotonic shock. Disruption of Aohex1 gene caused disappearance of Woronin bodies and the defect to prevent extensive loss of cytoplasm during hypotonic shock.« less

The protective effect of Rhizoma Dioscoreae extract against alveolar bone loss in ovariectomized rats via regulating Wnt and p38 MAPK signaling.

PubMed

Zhang, Zhiguo; Xiang, Lihua; Bai, Dong; Wang, Wenlai; Li, Yan; Pan, Jinghua; Liu, Hong; Wang, Shaojun; Xiao, Gary Guishan; Ju, Dahong

2014-12-12

The aim of this study was to evaluate the osteoprotective effect of aqueous Rhizoma Dioscoreae extract (RDE) on the alveolar bone of rats with ovariectomy-induced bone loss. Female Wistar rats were subjected to either ovariectomy or a sham operation (SHAM). The ovariectomized (OVX) rats were treated with vehicle (OVX) or RDE by oral gavage or with 17β-estradiol (E2) subcutaneously. After treatments, the bone mineral density (BMD), the three-dimensional bone architecture of the alveolar bone and the plasma biomarkers of bone turnover were analyzed to assess bone metabolism, and the histomorphometry of the alveolar bone was observed. Microarrays were used to evaluate gene expression profiles in alveolar bone from RDE-treated and OVX rats. The differential expression of genes was further analyzed using Ingenuity Pathway Analysis (IPA). The key findings were verified using real-time quantitative RT-PCR (qRT-PCR). Our results showed that RDE inhibited alveolar bone loss in OVX rats. Compared to the OVX rats, the RDE-treated rats showed upregulated expression levels of 207 genes and downregulated expression levels of 176 genes in the alveolar bone. The IPA showed that several genes had the potential to code for proteins that were involved in the Wnt/β-catenin signaling pathway (Wnt7a, Fzd2, Tcf3, Spp1, Frzb, Sfrp2 and Sfrp4) and the p38 MAPK signaling pathway (Il1rn and Mapk14). These experiments revealed that RDE could inhibit ovariectomy-induced alveolar bone loss in rats. The mechanism of this anti-osteopenic effect in alveolar bone may be involved in the reduced abnormal bone remodeling, which is associated with the modulation of the Wnt/β-catenin and the p38 MAPK signaling pathways via gene regulation.

Bi-Force: large-scale bicluster editing and its application to gene expression data biclustering

PubMed Central

Sun, Peng; Speicher, Nora K.; Röttger, Richard; Guo, Jiong; Baumbach, Jan

2014-01-01

Abstract The explosion of the biological data has dramatically reformed today's biological research. The need to integrate and analyze high-dimensional biological data on a large scale is driving the development of novel bioinformatics approaches. Biclustering, also known as ‘simultaneous clustering’ or ‘co-clustering’, has been successfully utilized to discover local patterns in gene expression data and similar biomedical data types. Here, we contribute a new heuristic: ‘Bi-Force’. It is based on the weighted bicluster editing model, to perform biclustering on arbitrary sets of biological entities, given any kind of pairwise similarities. We first evaluated the power of Bi-Force to solve dedicated bicluster editing problems by comparing Bi-Force with two existing algorithms in the BiCluE software package. We then followed a biclustering evaluation protocol in a recent review paper from Eren et al. (2013) (A comparative analysis of biclustering algorithms for gene expressiondata. Brief. Bioinform., 14:279–292.) and compared Bi-Force against eight existing tools: FABIA, QUBIC, Cheng and Church, Plaid, BiMax, Spectral, xMOTIFs and ISA. To this end, a suite of synthetic datasets as well as nine large gene expression datasets from Gene Expression Omnibus were analyzed. All resulting biclusters were subsequently investigated by Gene Ontology enrichment analysis to evaluate their biological relevance. The distinct theoretical foundation of Bi-Force (bicluster editing) is more powerful than strict biclustering. We thus outperformed existing tools with Bi-Force at least when following the evaluation protocols from Eren et al. Bi-Force is implemented in Java and integrated into the open source software package of BiCluE. The software as well as all used datasets are publicly available at http://biclue.mpi-inf.mpg.de. PMID:24682815

A novel feature extraction approach for microarray data based on multi-algorithm fusion

PubMed Central

Jiang, Zhu; Xu, Rong

2015-01-01

Feature extraction is one of the most important and effective method to reduce dimension in data mining, with emerging of high dimensional data such as microarray gene expression data. Feature extraction for gene selection, mainly serves two purposes. One is to identify certain disease-related genes. The other is to find a compact set of discriminative genes to build a pattern classifier with reduced complexity and improved generalization capabilities. Depending on the purpose of gene selection, two types of feature extraction algorithms including ranking-based feature extraction and set-based feature extraction are employed in microarray gene expression data analysis. In ranking-based feature extraction, features are evaluated on an individual basis, without considering inter-relationship between features in general, while set-based feature extraction evaluates features based on their role in a feature set by taking into account dependency between features. Just as learning methods, feature extraction has a problem in its generalization ability, which is robustness. However, the issue of robustness is often overlooked in feature extraction. In order to improve the accuracy and robustness of feature extraction for microarray data, a novel approach based on multi-algorithm fusion is proposed. By fusing different types of feature extraction algorithms to select the feature from the samples set, the proposed approach is able to improve feature extraction performance. The new approach is tested against gene expression dataset including Colon cancer data, CNS data, DLBCL data, and Leukemia data. The testing results show that the performance of this algorithm is better than existing solutions. PMID:25780277

A novel feature extraction approach for microarray data based on multi-algorithm fusion.

PubMed

Jiang, Zhu; Xu, Rong

2015-01-01

Feature extraction is one of the most important and effective method to reduce dimension in data mining, with emerging of high dimensional data such as microarray gene expression data. Feature extraction for gene selection, mainly serves two purposes. One is to identify certain disease-related genes. The other is to find a compact set of discriminative genes to build a pattern classifier with reduced complexity and improved generalization capabilities. Depending on the purpose of gene selection, two types of feature extraction algorithms including ranking-based feature extraction and set-based feature extraction are employed in microarray gene expression data analysis. In ranking-based feature extraction, features are evaluated on an individual basis, without considering inter-relationship between features in general, while set-based feature extraction evaluates features based on their role in a feature set by taking into account dependency between features. Just as learning methods, feature extraction has a problem in its generalization ability, which is robustness. However, the issue of robustness is often overlooked in feature extraction. In order to improve the accuracy and robustness of feature extraction for microarray data, a novel approach based on multi-algorithm fusion is proposed. By fusing different types of feature extraction algorithms to select the feature from the samples set, the proposed approach is able to improve feature extraction performance. The new approach is tested against gene expression dataset including Colon cancer data, CNS data, DLBCL data, and Leukemia data. The testing results show that the performance of this algorithm is better than existing solutions.

System for selecting relevant information for decision support.

PubMed

Kalina, Jan; Seidl, Libor; Zvára, Karel; Grünfeldová, Hana; Slovák, Dalibor; Zvárová, Jana

2013-01-01

We implemented a prototype of a decision support system called SIR which has a form of a web-based classification service for diagnostic decision support. The system has the ability to select the most relevant variables and to learn a classification rule, which is guaranteed to be suitable also for high-dimensional measurements. The classification system can be useful for clinicians in primary care to support their decision-making tasks with relevant information extracted from any available clinical study. The implemented prototype was tested on a sample of patients in a cardiological study and performs an information extraction from a high-dimensional set containing both clinical and gene expression data.

A Modified Consumer Inkjet for Spatiotemporal Control of Gene Expression

PubMed Central

Cohen, Daniel J.; Morfino, Roberto C.; Maharbiz, Michel M.

2009-01-01

This paper presents a low-cost inkjet dosing system capable of continuous, two-dimensional spatiotemporal regulation of gene expression via delivery of diffusible regulators to a custom-mounted gel culture of E. coli. A consumer-grade, inkjet printer was adapted for chemical printing; E. coli cultures were grown on 750 µm thick agar embedded in micro-wells machined into commercial compact discs. Spatio-temporal regulation of the lac operon was demonstrated via the printing of patterns of lactose and glucose directly into the cultures; X-Gal blue patterns were used for visual feedback. We demonstrate how the bistable nature of the lac operon's feedback, when perturbed by patterning lactose (inducer) and glucose (inhibitor), can lead to coordination of cell expression patterns across a field in ways that mimic motifs seen in developmental biology. Examples of this include sharp boundaries and the generation of traveling waves of mRNA expression. To our knowledge, this is the first demonstration of reaction-diffusion effects in the well-studied lac operon. A finite element reaction-diffusion model of the lac operon is also presented which predicts pattern formation with good fidelity. PMID:19763256

Molecular Validation of Chondrogenic Differentiation and Hypoxia Responsiveness of Platelet-Lysate Expanded Adipose Tissue-Derived Human Mesenchymal Stromal Cells.

PubMed

Galeano-Garces, Catalina; Camilleri, Emily T; Riester, Scott M; Dudakovic, Amel; Larson, Dirk R; Qu, Wenchun; Smith, Jay; Dietz, Allan B; Im, Hee-Jeong; Krych, Aaron J; Larson, A Noelle; Karperien, Marcel; van Wijnen, Andre J

2017-07-01

To determine the optimal environmental conditions for chondrogenic differentiation of human adipose tissue-derived mesenchymal stromal/stem cells (AMSCs). In this investigation we specifically investigate the role of oxygen tension and 3-dimensional (3D) culture systems. Both AMSCs and primary human chondrocytes were cultured for 21 days in chondrogenic media under normoxic (21% oxygen) or hypoxic (2% oxygen) conditions using 2 distinct 3D culture methods (high-density pellets and poly-ε-caprolactone [PCL] scaffolds). Histologic analysis of chondro-pellets and the expression of chondrocyte-related genes as measured by reverse transcriptase quantitative polymerase chain reaction were used to evaluate the efficiency of differentiation. AMSCs are capable of expressing established cartilage markers including COL2A1, ACAN, and DCN when grown in chondrogenic differentiation media as determined by gene expression and histologic analysis of cartilage markers. Expression of several cartilage-related genes was enhanced by low oxygen tension, including ACAN and HAPLN1. The pellet culture environment also promoted the expression of hypoxia-inducible cartilage markers compared with cells grown on 3D scaffolds. Cell type-specific effects of low oxygen and 3D environments indicate that mesenchymal cell fate and differentiation potential is remarkably sensitive to oxygen. Genetic programming of AMSCs to a chondrocytic phenotype is effective under hypoxic conditions as evidenced by increased expression of cartilage-related biomarkers and biosynthesis of a glycosaminoglycan-positive matrix. Lower local oxygen levels within cartilage pellets may be a significant driver of chondrogenic differentiation.

Differentially expressed genes and proteins upon drought acclimation in tolerant and sensitive genotypes of Coffea canephora

PubMed Central

Marraccini, Pierre; Vinecky, Felipe; Alves, Gabriel S.C.; Ramos, Humberto J.O.; Elbelt, Sonia; Vieira, Natalia G.; Carneiro, Fernanda A.; Sujii, Patricia S.; Alekcevetch, Jean C.; Silva, Vânia A.; DaMatta, Fábio M.; Ferrão, Maria A.G.; Leroy, Thierry; Pot, David; Vieira, Luiz G.E.; da Silva, Felipe R.; Andrade, Alan C.

2012-01-01

The aim of this study was to investigate the molecular mechanisms underlying drought acclimation in coffee plants by the identification of candidate genes (CGs) using different approaches. The first approach used the data generated during the Brazilian Coffee expressed sequence tag (EST) project to select 13 CGs by an in silico analysis (electronic northern). The second approach was based on screening macroarrays spotted with plasmid DNA (coffee ESTs) with separate hybridizations using leaf cDNA probes from drought-tolerant and susceptible clones of Coffea canephora var. Conilon, grown under different water regimes. This allowed the isolation of seven additional CGs. The third approach used two-dimensional gel electrophoresis to identify proteins displaying differential accumulation in leaves of drought-tolerant and susceptible clones of C. canephora. Six of them were characterized by MALDI-TOF-MS/MS (matrix-assisted laser desorption-time of flight-tandem mass spectrometry) and the corresponding proteins were identified. Finally, additional CGs were selected from the literature, and quantitative real-time polymerase chain reaction (qPCR) was performed to analyse the expression of all identified CGs. Altogether, >40 genes presenting differential gene expression during drought acclimation were identified, some of them showing different expression profiles between drought-tolerant and susceptible clones. Based on the obtained results, it can be concluded that factors involved a complex network of responses probably involving the abscisic signalling pathway and nitric oxide are major molecular determinants that might explain the better efficiency in controlling stomata closure and transpiration displayed by drought-tolerant clones of C. canephora. PMID:22511801

Beyond the known functions of the CCR4-NOT complex in gene expression regulatory mechanisms: New structural insights to unravel CCR4-NOT mRNA processing machinery.

PubMed

Ukleja, Marta; Valpuesta, José María; Dziembowski, Andrzej; Cuellar, Jorge

2016-10-01

Large protein assemblies are usually the effectors of major cellular processes. The intricate cell homeostasis network is divided into numerous interconnected pathways, each controlled by a set of protein machines. One of these master regulators is the CCR4-NOT complex, which ultimately controls protein expression levels. This multisubunit complex assembles around a scaffold platform, which enables a wide variety of well-studied functions from mRNA synthesis to transcript decay, as well as other tasks still being identified. Solving the structure of the entire CCR4-NOT complex will help to define the distribution of its functions. The recently published three-dimensional reconstruction of the complex, in combination with the known crystal structures of some of the components, has begun to address this. Methodological improvements in structural biology, especially in cryoelectron microscopy, encourage further structural and protein-protein interaction studies, which will advance our comprehension of the gene expression machinery. © 2016 WILEY Periodicals, Inc.

An Adult Mouse Thyroid Side Population Cell Line that Exhibits Enriched Epithelial–Mesenchymal Transition

PubMed Central

Murata, Tsubasa; Iwadate, Manabu; Takizawa, Yoshinori; Miyakoshi, Masaaki; Hayase, Suguru; Yang, Wenjing; Cai, Yan; Yokoyama, Shigetoshi; Nagashima, Kunio; Wakabayashi, Yoshiyuki; Zhu, Jun

2017-01-01

Background: Studies of thyroid stem/progenitor cells have been hampered due to the small organ size and lack of tissue, which limits the yield of these cells. A continuous source that allows the study and characterization of thyroid stem/progenitor cells is desired to push the field forward. Method: A cell line was established from Hoechst-resistant side population cells derived from mouse thyroid that were previously shown to contain stem/progenitor-like cells. Characterization of these cells were carried out by using in vitro two- and three-dimensional cultures and in vivo reconstitution of mice after orthotopic or intravenous injection, in conjunction with quantitative reverse transcription polymerase chain reaction, Western blotting, immunohisto(cyto)chemistry/immunofluorescence, and RNA seq analysis. Results: These cells were named SPTL (side population cell-derived thyroid cell line). Under low serum culturing conditions, SPTL cells expressed the thyroid differentiation marker NKX2-1, a transcription factor critical for thyroid differentiation and function, while no expression of other thyroid differentiation marker genes were observed. SPTL cells formed follicle-like structures in Matrigel® cultures, which did not express thyroid differentiation marker genes. In mouse models of orthotopic and intravenous injection, the latter following partial thyroidectomy, a few SPTL cells were found in part of the follicles, most of which expressed NKX2-1. SPTL cells highly express genes involved in epithelial–mesenchymal transition, as demonstrated by RNA seq analysis, and exhibit a gene-expression pattern similar to anaplastic thyroid carcinoma. Conclusion: These results demonstrate that SPTL cells have the capacity to differentiate into thyroid to a limited degree. SPTL cells may provide an excellent tool to study stem cells, including cancer stem cells of the thyroid. PMID:28125936

Balancing Cell Migration with Matrix Degradation Enhances Gene Delivery to Cells Cultured Three-Dimensionally Within Hydrogels

PubMed Central

Shepard, Jaclyn A.; Huang, Alyssa; Shikanova, Ariella; Shea, Lonnie D.

2010-01-01

In regenerative medicine, hydrogels are employed to fill defects and support the infiltration of cells that can ultimately regenerate tissue. Gene delivery within hydrogels targeting infiltrating cells has the potential to promote tissue formation, but the delivery efficiency of nonviral vectors within hydrogels is low hindering their applicability in tissue regeneration. To improve their functionality, we have conducted a mechanistic study to investigate the contribution of cell migration and matrix degradation on gene delivery. In this report, lipoplexes were entrapped within hydrogels based on poly(ethylene glycol) (PEG) crosslinked with peptides containing matrix metalloproteinase degradable sequences. The mesh size of these hydrogels is substantially less than the size of the entrapped lipoplexes, which can function to retain vectors. Cell migration and transfection were simultaneously measured within hydrogels with varying density of cell adhesion sites (Arg-Gly-Asp peptides) and solids content. Increasing RGD density increased expression levels up to 100-fold, while greater solids content sustained expression levels for 16 days. Increasing RGD density and decreasing solids content increased cell migration, which indicates expression levels increase with increased cell migration. Initially exposing cells to vector resulted in transient expression that declined after 2 days, verifying the requirement of migration to sustain expression. Transfected cells were predominantly located within the population of migrating cells for hydrogels that supported cell migration. Although the small mesh size retained at least 70% of the lipoplexes in the absence of cells after 32 days, the presence of cells decreased retention to 10% after 16 days. These results indicate that vectors retained within hydrogels contact migrating cells, and that persistent cell migration can maintain elevated expression levels. Thus matrix degradation and cell migration are fundamental design parameters for maximizing gene delivery from hydrogels. PMID:20450944

Improved high-dimensional prediction with Random Forests by the use of co-data.

PubMed

Te Beest, Dennis E; Mes, Steven W; Wilting, Saskia M; Brakenhoff, Ruud H; van de Wiel, Mark A

2017-12-28

Prediction in high dimensional settings is difficult due to the large number of variables relative to the sample size. We demonstrate how auxiliary 'co-data' can be used to improve the performance of a Random Forest in such a setting. Co-data are incorporated in the Random Forest by replacing the uniform sampling probabilities that are used to draw candidate variables by co-data moderated sampling probabilities. Co-data here are defined as any type information that is available on the variables of the primary data, but does not use its response labels. These moderated sampling probabilities are, inspired by empirical Bayes, learned from the data at hand. We demonstrate the co-data moderated Random Forest (CoRF) with two examples. In the first example we aim to predict the presence of a lymph node metastasis with gene expression data. We demonstrate how a set of external p-values, a gene signature, and the correlation between gene expression and DNA copy number can improve the predictive performance. In the second example we demonstrate how the prediction of cervical (pre-)cancer with methylation data can be improved by including the location of the probe relative to the known CpG islands, the number of CpG sites targeted by a probe, and a set of p-values from a related study. The proposed method is able to utilize auxiliary co-data to improve the performance of a Random Forest.

High level expression and characterization of the cyclophilin B gene from the anaerobic fungus Orpinomyces sp. strain PC-2.

PubMed

Chen, Huizhong; Li, Xin-Liang; Xu, Haiyan; Ljungdahl, Lars G; Cerniglia, Carl E

2006-01-01

Cyclophilins are an evolutionarily conserved family of peptidyl-prolyl cis-trans isomerases (PPIases). A cyclophilin B (cypB) gene from the anaerobic fungus Orpinomyces sp. strain PC-2 was cloned and overexpressed in Escherichia coli. It was expressed as an amino-terminal 6 x His-tagged recombinant protein to facilitate purification. Highly purified protein (26.5 kDa) was isolated by two chromatographic steps involving affinity and gel filtration for biochemical studies of the enzyme. The recombinant CypB displayed PPIase activity with a k(cat)/K(m) of 8.9 x 10(6) M(-1) s(-1) at 10 degrees C and pH 7.8. It was inhibited by cyclosporin A (CsA) with an IC(50) of 23.5 nM, similar to those of the native protein and other cyclophilin B enzymes from animals. Genomic DNA analysis of cypB revealed that it was present as a single copy in Orpinomyces PC-2 and contained two introns, indicating it has a eukaryotic origin. It is one of the most heavily interrupted genes with intron sequences found in anaerobic fungi. The three-dimensional model of Orpinomyces PC-2 CypB was predicted with a homology modeling approach using the Swiss-Model Protein Modeling Server and three dimensional structure of human CypB as a template. The overall architecture of the CypB molecule is very similar to that of human CypB.

Integrative sparse principal component analysis of gene expression data.

PubMed

Liu, Mengque; Fan, Xinyan; Fang, Kuangnan; Zhang, Qingzhao; Ma, Shuangge

2017-12-01

In the analysis of gene expression data, dimension reduction techniques have been extensively adopted. The most popular one is perhaps the PCA (principal component analysis). To generate more reliable and more interpretable results, the SPCA (sparse PCA) technique has been developed. With the "small sample size, high dimensionality" characteristic of gene expression data, the analysis results generated from a single dataset are often unsatisfactory. Under contexts other than dimension reduction, integrative analysis techniques, which jointly analyze the raw data of multiple independent datasets, have been developed and shown to outperform "classic" meta-analysis and other multidatasets techniques and single-dataset analysis. In this study, we conduct integrative analysis by developing the iSPCA (integrative SPCA) method. iSPCA achieves the selection and estimation of sparse loadings using a group penalty. To take advantage of the similarity across datasets and generate more accurate results, we further impose contrasted penalties. Different penalties are proposed to accommodate different data conditions. Extensive simulations show that iSPCA outperforms the alternatives under a wide spectrum of settings. The analysis of breast cancer and pancreatic cancer data further shows iSPCA's satisfactory performance. © 2017 WILEY PERIODICALS, INC.

Integrating multiple molecular sources into a clinical risk prediction signature by extracting complementary information.

PubMed

Hieke, Stefanie; Benner, Axel; Schlenl, Richard F; Schumacher, Martin; Bullinger, Lars; Binder, Harald

2016-08-30

High-throughput technology allows for genome-wide measurements at different molecular levels for the same patient, e.g. single nucleotide polymorphisms (SNPs) and gene expression. Correspondingly, it might be beneficial to also integrate complementary information from different molecular levels when building multivariable risk prediction models for a clinical endpoint, such as treatment response or survival. Unfortunately, such a high-dimensional modeling task will often be complicated by a limited overlap of molecular measurements at different levels between patients, i.e. measurements from all molecular levels are available only for a smaller proportion of patients. We propose a sequential strategy for building clinical risk prediction models that integrate genome-wide measurements from two molecular levels in a complementary way. To deal with partial overlap, we develop an imputation approach that allows us to use all available data. This approach is investigated in two acute myeloid leukemia applications combining gene expression with either SNP or DNA methylation data. After obtaining a sparse risk prediction signature e.g. from SNP data, an automatically selected set of prognostic SNPs, by componentwise likelihood-based boosting, imputation is performed for the corresponding linear predictor by a linking model that incorporates e.g. gene expression measurements. The imputed linear predictor is then used for adjustment when building a prognostic signature from the gene expression data. For evaluation, we consider stability, as quantified by inclusion frequencies across resampling data sets. Despite an extremely small overlap in the application example with gene expression and SNPs, several genes are seen to be more stably identified when taking the (imputed) linear predictor from the SNP data into account. In the application with gene expression and DNA methylation, prediction performance with respect to survival also indicates that the proposed approach might work well. We consider imputation of linear predictor values to be a feasible and sensible approach for dealing with partial overlap in complementary integrative analysis of molecular measurements at different levels. More generally, these results indicate that a complementary strategy for integrating different molecular levels can result in more stable risk prediction signatures, potentially providing a more reliable insight into the underlying biology.

Annotated Gene and Proteome Data Support Recognition of Interconnections Between the Results of Different Experiments in Space Research

NASA Astrophysics Data System (ADS)

Bauer, Johann; Wehland, Markus; Pietsch, Jessica; Sickmann, Albert; Weber, Gerhard; Grimm, Daniela

2016-06-01

In a series of studies, human thyroid and endothelial cells exposed to real or simulated microgravity were analyzed in terms of changes in gene expression patterns or protein content. Due to the limitation of available cells in many space research experiments, comparative and control experiments had to be done in a serial manner. Therefore, detected genes or proteins were annotated with gene names and SwissProt numbers, in order to allow searches for interconnections between results obtained in different experiments by different methods. A crosscheck of several studies on the behavior of cytoskeletal genes and proteins suggested that clusters of cytoskeletal components change differently under the influence of microgravity and/or vibration in different cell types. The result that LOX and ISG15 gene expression were clearly altered during the Shenzhou-8 spaceflight mission could be estimated by comparison with the results of other experiments. The more than 100-fold down-regulation of LOX supports our hypothesis that the amount and stability of extracellular matrix have a great influence on the formation of three-dimensional aggregates under microgravity. The approximately 40-fold up-regulation of ISG15 cannot yet be explained in detail, but strongly suggests that ISGylation, an alternative form of posttranslational modification, plays a role in longterm cultures.

Genes regulated by AoXlnR, the xylanolytic and cellulolytic transcriptional regulator, in Aspergillus oryzae.

PubMed

Noguchi, Yuji; Sano, Motoaki; Kanamaru, Kyoko; Ko, Taro; Takeuchi, Michio; Kato, Masashi; Kobayashi, Tetsuo

2009-11-01

XlnR is a Zn(II)2Cys6 transcriptional activator of xylanolytic and cellulolytic genes in Aspergillus. Overexpression of the aoxlnR gene in Aspergillus oryzae (A. oryzae xlnR gene) resulted in elevated xylanolytic and cellulolytic activities in the culture supernatant, in which nearly 40 secreted proteins were detected by two-dimensional electrophoresis. DNA microarray analysis to identify the transcriptional targets of AoXlnR led to the identification of 75 genes that showed more than fivefold increase in their expression in the AoXlnR overproducer than in the disruptant. Of these, 32 genes were predicted to encode a glycoside hydrolase, highlighting the biotechnological importance of AoXlnR in biomass degradation. The 75 genes included the genes previously identified as AoXlnR targets (xynF1, xynF3, xynG2, xylA, celA, celB, celC, and celD). Thirty-six genes were predicted to be extracellular, which was consistent with the number of proteins secreted, and 61 genes possessed putative XlnR-binding sites (5'-GGCTAA-3', 5'-GGCTAG-3', and 5'-GGCTGA-3') in their promoter regions. Functional annotation of the genes revealed that AoXlnR regulated the expression of hydrolytic genes for degradation of beta-1,4-xylan, arabinoxylan, cellulose, and xyloglucan and of catabolic genes for the conversion of D-xylose to xylulose-5-phosphate. In addition, genes encoding glucose-6-phosphate 1-dehydrogenase and L-arabinitol-4- dehydrogenase involved in D-glucose and L-arabinose catabolism also appeared to be targets of AoXlnR.

Local sparse bump hunting reveals molecular heterogeneity of colon tumors‡

PubMed Central

Dazard, Jean-Eudes; Rao, J. Sunil; Markowitz, Sanford

2013-01-01

The question of molecular heterogeneity and of tumoral phenotype in cancer remains unresolved. To understand the underlying molecular basis of this phenomenon, we analyzed genome-wide expression data of colon cancer metastasis samples, as these tumors are the most advanced and hence would be anticipated to be the most likely heterogeneous group of tumors, potentially exhibiting the maximum amount of genetic heterogeneity. Casting a statistical net around such a complex problem proves difficult because of the high dimensionality and multi-collinearity of the gene expression space, combined with the fact that genes act in concert with one another and that not all genes surveyed might be involved. We devise a strategy to identify distinct subgroups of samples and determine the genetic/molecular signature that defines them. This involves use of the local sparse bump hunting algorithm, which provides a much more optimal and biologically faithful transformed space within which to search for bumps. In addition, thanks to the variable selection feature of the algorithm, we derived a novel sparse gene expression signature, which appears to divide all colon cancer patients into two populations: a population whose expression pattern can be molecularly encompassed within the bump and an outlier population that cannot be. Although all patients within any given stage of the disease, including the metastatic group, appear clinically homogeneous, our procedure revealed two subgroups in each stage with distinct genetic/molecular profiles. We also discuss implications of such a finding in terms of early detection, diagnosis and prognosis. PMID:22052459

Projecting 2D gene expression data into 3D and 4D space.

PubMed

Gerth, Victor E; Katsuyama, Kaori; Snyder, Kevin A; Bowes, Jeff B; Kitayama, Atsushi; Ueno, Naoto; Vize, Peter D

2007-04-01

Video games typically generate virtual 3D objects by texture mapping an image onto a 3D polygonal frame. The feeling of movement is then achieved by mathematically simulating camera movement relative to the polygonal frame. We have built customized scripts that adapt video game authoring software to texture mapping images of gene expression data onto b-spline based embryo models. This approach, known as UV mapping, associates two-dimensional (U and V) coordinates within images to the three dimensions (X, Y, and Z) of a b-spline model. B-spline model frameworks were built either from confocal data or de novo extracted from 2D images, once again using video game authoring approaches. This system was then used to build 3D models of 182 genes expressed in developing Xenopus embryos and to implement these in a web-accessible database. Models can be viewed via simple Internet browsers and utilize openGL hardware acceleration via a Shockwave plugin. Not only does this database display static data in a dynamic and scalable manner, the UV mapping system also serves as a method to align different images to a common framework, an approach that may make high-throughput automated comparisons of gene expression patterns possible. Finally, video game systems also have elegant methods for handling movement, allowing biomechanical algorithms to drive the animation of models. With further development, these biomechanical techniques offer practical methods for generating virtual embryos that recapitulate morphogenesis.

Mechanical activation of mammalian target of rapamycin pathway is required for cartilage development

PubMed Central

Guan, Yingjie; Yang, Xu; Yang, Wentian; Charbonneau, Cherie; Chen, Qian

2014-01-01

Mechanical stress regulates development by modulating cell signaling and gene expression. However, the cytoplasmic components mediating mechanotransduction remain unclear. In this study, elimination of muscle contraction during chicken embryonic development resulted in a reduction in the activity of mammalian target of rapamycin (mTOR) in the cartilaginous growth plate. Inhibition of mTOR activity led to significant inhibition of chondrocyte proliferation, cartilage tissue growth, and expression of chondrogenic genes, including Indian hedgehog (Ihh), a critical mediator of mechanotransduction. Conversely, cyclic loading (1 Hz, 5% matrix deformation) of embryonic chicken growth plate chondrocytes in 3-dimensional (3D) collagen scaffolding induced sustained activation of mTOR. Mechanical activation of mTOR occurred in serum-free medium, indicating that it is independent of growth factor or nutrients. Treatment of chondrocytes with Rapa abolished mechanical activation of cell proliferation and Ihh gene expression. Cyclic loading of chondroprogenitor cells deficient in SH2-containing protein tyrosine phosphatase 2 (Shp2) further enhanced mechanical activation of mTOR, cell proliferation, and chondrogenic gene expression. This result suggests that Shp2 is an antagonist of mechanotransduction through inhibition of mTOR activity. Our data demonstrate that mechanical activation of mTOR is necessary for cell proliferation, chondrogenesis, and cartilage growth during bone development, and that mTOR is an essential mechanotransduction component modulated by Shp2 in the cytoplasm.—Guan, Y., Yang, X., Yang, W., Charbonneau, C., Chen, Q. Mechanical activation of mammalian target of rapamycin pathway is required for cartilage development. PMID:25002119

The PA influenza virus polymerase subunit is a phosphorylated protein.

PubMed

Sanz-Ezquerro, J J; Fernández Santarén, J; Sierra, T; Aragón, T; Ortega, J; Ortín, J; Smith, G L; Nieto, A

1998-03-01

The induction of proteolysis by expression of the influenza virus PA polymerase subunit is the only biochemical activity ascribed to this protein. In the course of studying viral protein synthesis by two-dimensional gel electrophoresis, we observed the existence of several PA isoforms with different isoelectric points. These isoforms were also present when the PA gene was singly expressed in three different expression systems, indicating that a cellular activity is responsible for its post-translational modification. In vivo labelling with [32P]orthophosphate, followed by two-dimensional gel electrophoresis, clearly demonstrated the incorporation of phosphate into the PA molecule. Phosphoserine and phosphothreonine epitopes were present in PA, while phosphotyrosine residues were absent, as tested by immunoblotting with specific antibodies. These facts, as well as the presence of multiple consensus sites for casein kinase II (CKII) phosphorylation, prompted us to test the involvement of this kinase in PA covalent modification. PA protein purified by immunoprecipitation could be specifically labelled by the catalytic alpha subunit of human CKII, which was expressed and purified from bacteria. Collectively, these data demonstrate that the PA subunit of the influenza virus RNA polymerase is a phosphoprotein.

Sunflower (Helianthus annuus) fatty acid synthase complex: β-hydroxyacyl-[acyl carrier protein] dehydratase genes.

PubMed

González-Thuillier, Irene; Venegas-Calerón, Mónica; Sánchez, Rosario; Garcés, Rafael; von Wettstein-Knowles, Penny; Martínez-Force, Enrique

2016-02-01

Two sunflower hydroxyacyl-[acyl carrier protein] dehydratases evolved into two different isoenzymes showing distinctive expression levels and kinetics' efficiencies. β-Hydroxyacyl-[acyl carrier protein (ACP)]-dehydratase (HAD) is a component of the type II fatty acid synthase complex involved in 'de novo' fatty acid biosynthesis in plants. This complex, formed by four intraplastidial proteins, is responsible for the sequential condensation of two-carbon units, leading to 16- and 18-C acyl-ACP. HAD dehydrates 3-hydroxyacyl-ACP generating trans-2-enoyl-ACP. With the aim of a further understanding of fatty acid biosynthesis in sunflower (Helianthus annuus) seeds, two β-hydroxyacyl-[ACP] dehydratase genes have been cloned from developing seeds, HaHAD1 (GenBank HM044767) and HaHAD2 (GenBank GU595454). Genomic DNA gel blot analyses suggest that both are single copy genes. Differences in their expression patterns across plant tissues were detected. Higher levels of HaHAD2 in the initial stages of seed development inferred its key role in seed storage fatty acid synthesis. That HaHAD1 expression levels remained constant across most tissues suggest a housekeeping function. Heterologous expression of these genes in E. coli confirmed both proteins were functional and able to interact with the bacterial complex 'in vivo'. The large increase of saturated fatty acids in cells expressing HaHAD1 and HaHAD2 supports the idea that these HAD genes are closely related to the E. coli FabZ gene. The proposed three-dimensional models of HaHAD1 and HaHAD2 revealed differences at the entrance to the catalytic tunnel attributable to Phe166/Val1159, respectively. HaHAD1 F166V was generated to study the function of this residue. The 'in vitro' enzymatic characterization of the three HAD proteins demonstrated all were active, with the mutant having intermediate K m and V max values to the wild-type proteins.

Regulation of gene expression in intervertebral disc cells by low and high hydrostatic pressure.

PubMed

Neidlinger-Wilke, Cornelia; Würtz, Karin; Urban, Jill P G; Börm, Wolfgang; Arand, Markus; Ignatius, Anita; Wilke, Hans-Joachim; Claes, Lutz E

2006-08-01

Intervertebral disc structures are exposed to wide ranges of intradiscal hydrostatic pressure during different loading exercises and are at their minimum during lying or relaxed sitting and at maximum during lifting weights with a round back. We hypothesize that these different loading magnitudes influence the intervertebral disc (IVD) by alteration of disc matrix turnover depending on their magnitudes. Therefore the aim of this study was to assess changes in gene expression of human nucleus cells after the application of low hydrostatic pressure (0.25 MPa) and high hydrostatic pressure (2.5 MPa). IVD cells isolated from the nucleus of human (n = 18) and bovine (n = 24 from four animals) disc biopsies were seeded into three-dimensional collagen type-I matrices and exposed to the different loading magnitudes by specially developed pressure chambers. The lower pressure range (0.25 MPa, 30 min, 0.1 Hz) was applied with a recently published device by using an external compression cylinder. For the application of higher loads (2.5 MPa, 30 min, 0.1 Hz) the cell-loaded collagen gels were sealed into sterile bags with culture medium and stimulated in a newly developed water-filled compression cylinder by using a loading frame. These methods allowed the comparison of loading regimes in a wide physiological range under an equal three-dimensional culture conditions. Cells were harvested 24 h after the end of stimulation and changes in the expression of genes known to influence IVD matrix turnover (collagen-I, collagen-II, aggrecan, MMP1, MMP2, MMP3, MMP13) were analyzed by real-time RT-PCR. A Wilcoxon signed-rank test(1) and a Wilcoxon 2-sample test(2) were performed to detect differences between the stimulated and control samples(1) and differences between low and high hydrostatic pressure(2). Multiple testing was considered by adjusting the p value appropriately. Both regimes of hydrostatic pressure influenced gene expression in nucleus cells with opposite tendencies for the matrix forming proteins aggrecan and collagen type-I in response to the two different pressure magnitudes: Low hydrostatic-pressure (0.25 MPa) tended to increase collagen-I and aggrecan expression of human nucleus cells (P < 0.05) but only to a small degree. High hydrostatic pressure (2.5 MPa) tended to decrease gene expression of all anabolic proteins with significant effects on aggrecan expression of nucleus cells (P = 0.004). Low hydrostatic pressure had no influence on the expression of matrix metalloproteinases (MMP1, MMP2, MMP3 and MMP13). In contrast, high hydrostatic pressure tended to increase the expression of MMP1, MMP3 and MMP13 of human nucleus cells with high individual-individual variations. The decreased expression of aggrecan (P = 0.008) and collagen type II (P = 0.023) and the increased MMP3 expression (P = 0.008) in response to high hydrostatic pressure could be confirmed in additional experiments with bovine nucleus cells. These results suggest that hydrostatic pressure as one of the physiological stimuli of the IVD may influence matrix turnover in a magnitude dependent way. Low hydrostatic pressure (0.25 MPa) has quite small influences with a tendency to anabolic effects, whereas high hydrostatic pressure (2.5 MPa) tends to decrease the matrix protein expression with a tendency to increase some matrix-turnover enzymes. Therefore, hydrostatic pressure may regulate disc matrix turnover in a dose-dependent way.

Differences in shotgun protein expression profile between superficial bladder transitional cell carcinoma and normal urothelium.

PubMed

Niu, Hai Tao; Zhang, Yi Bing; Jiang, Hai Ping; Cheng, Bo; Sun, Guang; Wang, Yi; E, Ya Jun; Pang, De Quan; Chang, Ji Wu

2009-01-01

This study was undertaken to identify differences in protein expression profiles between superficial bladder transitional cell carcinoma (BTCC) and normal urothelial cells. We used laser capture microdissection (LCM) to harvest purified cells, and used two-dimensional liquid chromatography (2D-LC) followed by electrospray ionization-tandem mass spectrometry (ESI-MS/MS) to separate and identify the peptide mixture. A total of 440/438 proteins commonly appeared in 4 paired specimens. Multi-step bioinformatic procedures were used for the analysis of identified proteins; 175/179 of the 293/287 proteins that were specific expressed in tumor/normal cells own gene ontology (GO) biological process annotation. Compared with the entire list of the international protein index (IPI), there are 52/46 GO terms exhibited as enriched and 6/10 exhibited as depleted, respectively. Significantly altered pathways between tumor and normal cells mainly include oxidative phosphorylation, focal adhesion, etc. Finally, descriptive statistics show that the shotgun proteomics strategy has practice directive significance for biomarker discovery by two-dimensional electrophoresis (2-DE) technology.

Electrochemical synthesis of three-dimensional porous reduced graphene oxide film: Preparation and in vitro osteogenic activity evaluation.

PubMed

Tian, Zizhu; Huang, Lixun; Pei, Xibo; Chen, Junyu; Wang, Tong; Yang, Tao; Qin, Han; Sui, Lei; Wang, Jian

2017-07-01

In this study, three-dimensional reduced graphene oxide (3D-rGO) porous films were fabricated using a two-step electrochemical method, including an electrochemical deposition process for the self-assembly of GO and an electrochemical bubbling-based transfer. The morphology, physical properties, and phase composition of the 3D-rGO films were characterized, and the cellular bioactivities were evaluated using pre-osteoblasts (MC3T3-E1 cells). The attachment, proliferation and differentiation of the MC3T3-E1 cells on the 3D-rGO films was analyzed by scanning electron microscopy (SEM), Cell Counting Kit-8 (CCK-8) assays and live/dead cell staining, and alkaline phosphatase (ALP) activity assays, respectively. The expression of osteogenic-related genes in MC3T3-E1 cells was evaluated by reverse transcription-polymerase chain reaction (RT-PCR). The results showed that the 3D-rGO films supported cell viability and proliferation, as well as significantly enhanced ALP activity and osteogenic-related genes (ALP, OPN, Runx2) expressions. Our findings indicate the promising potential of the 3D-rGO porous films for bone tissue engineering. Copyright © 2017 Elsevier B.V. All rights reserved.

Global study of holistic morphological effectors in the budding yeast Saccharomyces cerevisiae.

PubMed

Suzuki, Godai; Wang, Yang; Kubo, Karen; Hirata, Eri; Ohnuki, Shinsuke; Ohya, Yoshikazu

2018-02-20

The size of the phenotypic effect of a gene has been thoroughly investigated in terms of fitness and specific morphological traits in the budding yeast Saccharomyces cerevisiae, but little is known about gross morphological abnormalities. We identified 1126 holistic morphological effectors that cause severe gross morphological abnormality when deleted, and 2241 specific morphological effectors with weak holistic effects but distinctive effects on yeast morphology. Holistic effectors fell into many gene function categories and acted as network hubs, affecting a large number of morphological traits, interacting with a large number of genes, and facilitating high protein expression. Holistic morphological abnormality was useful for estimating the importance of a gene to morphology. The contribution of gene importance to fitness and morphology could be used to efficiently classify genes into functional groups. Holistic morphological abnormality can be used as a reproducible and reliable gene feature for high-dimensional morphological phenotyping. It can be used in many functional genomic applications.

Zebrafish fin immune responses during high mortality infections with viral haemorrhagic septicemia rhabdovirus. A proteomic and transcriptomic approach.

PubMed

Encinas, Paloma; Rodriguez-Milla, Miguel A; Novoa, Beatriz; Estepa, Amparo; Figueras, Antonio; Coll, Julio

2010-09-27

Despite rhabdoviral infections being one of the best known fish diseases, the gene expression changes induced at the surface tissues after the natural route of infection (infection-by-immersion) have not been described yet. This work describes the differential infected versus non-infected expression of proteins and immune-related transcripts in fins and organs of zebrafish Danio rerio shortly after infection-by-immersion with viral haemorrhagic septicemia virus (VHSV). Two-dimensional differential gel electrophoresis detected variations on the protein levels of the enzymes of the glycolytic pathway and cytoskeleton components but it detected very few immune-related proteins. Differential expression of immune-related gene transcripts estimated by quantitative polymerase chain reaction arrays and hybridization to oligo microarrays showed that while more transcripts increased in fins than in organs (spleen, head kidney and liver), more transcripts decreased in organs than in fins. Increased differential transcript levels in fins detected by both arrays corresponded to previously described infection-related genes such as complement components (c3b, c8 and c9) or class I histocompatibility antigens (mhc1) and to newly described genes such as secreted immunoglobulin domain (sid4), macrophage stimulating factor (mst1) and a cluster differentiation antigen (cd36). The genes described would contribute to the knowledge of the earliest molecular events occurring in the fish surfaces at the beginning of natural rhabdoviral infections and/or might be new candidates to be tested as adjuvants for fish vaccines.

Evaluation of the osteo-inductive potential of hollow three-dimensional magnesium-strontium substitutes for the bone grafting application.

PubMed

Li, Mei; Yang, Xuan; Wang, Weidan; Zhang, Yu; Wan, Peng; Yang, Ke; Han, Yong

2017-04-01

Regeneration of bone defects is a clinical challenge that usually necessitates bone grafting materials. Limited bone supply and donor site morbidity limited the application of autografting, and improved biomaterials are needed to match the performance of autografts. Osteoinductive materials would be the perfect candidates for achieving this task. Strontium (Sr) is known to encourage bone formation and also prevent osteoporosis. Such twin requirements have motivated researchers to develop Sr-substituted biomaterials for orthopedic applications. The present study demonstrated a new concept of developing biodegradable and hollow three-dimensional magnesium-strontium (MgSr) devices for grafting with their clinical demands. The microstructure and performance of MgSr devices, in vitro degradation and biological properties including in vitro cytocompatibility and osteoinductivity were investigated. The results showed that our MgSr devices exhibited good cytocompatibility and osteogenic effect. To further investigate the underlying mechanisms, RT-PCR and Western Blotting assays were taken to analyze the expression level of osteogenesis-related genes and proteins, respectively. The results showed that our MgSr devices could both up-regulate the genes and proteins expression of the transcription factors of Runt-related transcription factor 2 (RUNX2) and Osterix (OSX), as well as alkaline phosphatase (ALP), Osteopontin (OPN), Collagen I (COL I) and Osteocalcin (OCN) significantly. Taken together, our innovation presented in this work demonstrated that the hollow three-dimensional MgSr substitutes had excellent biocompatibility and osteogenesis and could be potential candidates for bone grafting for future orthopedic applications. Copyright © 2016 Elsevier B.V. All rights reserved.

Bit-Table Based Biclustering and Frequent Closed Itemset Mining in High-Dimensional Binary Data

PubMed Central

Király, András; Abonyi, János

2014-01-01

During the last decade various algorithms have been developed and proposed for discovering overlapping clusters in high-dimensional data. The two most prominent application fields in this research, proposed independently, are frequent itemset mining (developed for market basket data) and biclustering (applied to gene expression data analysis). The common limitation of both methodologies is the limited applicability for very large binary data sets. In this paper we propose a novel and efficient method to find both frequent closed itemsets and biclusters in high-dimensional binary data. The method is based on simple but very powerful matrix and vector multiplication approaches that ensure that all patterns can be discovered in a fast manner. The proposed algorithm has been implemented in the commonly used MATLAB environment and freely available for researchers. PMID:24616651

Feature weight estimation for gene selection: a local hyperlinear learning approach

PubMed Central

2014-01-01

Background Modeling high-dimensional data involving thousands of variables is particularly important for gene expression profiling experiments, nevertheless,it remains a challenging task. One of the challenges is to implement an effective method for selecting a small set of relevant genes, buried in high-dimensional irrelevant noises. RELIEF is a popular and widely used approach for feature selection owing to its low computational cost and high accuracy. However, RELIEF based methods suffer from instability, especially in the presence of noisy and/or high-dimensional outliers. Results We propose an innovative feature weighting algorithm, called LHR, to select informative genes from highly noisy data. LHR is based on RELIEF for feature weighting using classical margin maximization. The key idea of LHR is to estimate the feature weights through local approximation rather than global measurement, which is typically used in existing methods. The weights obtained by our method are very robust in terms of degradation of noisy features, even those with vast dimensions. To demonstrate the performance of our method, extensive experiments involving classification tests have been carried out on both synthetic and real microarray benchmark datasets by combining the proposed technique with standard classifiers, including the support vector machine (SVM), k-nearest neighbor (KNN), hyperplane k-nearest neighbor (HKNN), linear discriminant analysis (LDA) and naive Bayes (NB). Conclusion Experiments on both synthetic and real-world datasets demonstrate the superior performance of the proposed feature selection method combined with supervised learning in three aspects: 1) high classification accuracy, 2) excellent robustness to noise and 3) good stability using to various classification algorithms. PMID:24625071

dictyExpress: a web-based platform for sequence data management and analytics in Dictyostelium and beyond.

PubMed

Stajdohar, Miha; Rosengarten, Rafael D; Kokosar, Janez; Jeran, Luka; Blenkus, Domen; Shaulsky, Gad; Zupan, Blaz

2017-06-02

Dictyostelium discoideum, a soil-dwelling social amoeba, is a model for the study of numerous biological processes. Research in the field has benefited mightily from the adoption of next-generation sequencing for genomics and transcriptomics. Dictyostelium biologists now face the widespread challenges of analyzing and exploring high dimensional data sets to generate hypotheses and discovering novel insights. We present dictyExpress (2.0), a web application designed for exploratory analysis of gene expression data, as well as data from related experiments such as Chromatin Immunoprecipitation sequencing (ChIP-Seq). The application features visualization modules that include time course expression profiles, clustering, gene ontology enrichment analysis, differential expression analysis and comparison of experiments. All visualizations are interactive and interconnected, such that the selection of genes in one module propagates instantly to visualizations in other modules. dictyExpress currently stores the data from over 800 Dictyostelium experiments and is embedded within a general-purpose software framework for management of next-generation sequencing data. dictyExpress allows users to explore their data in a broader context by reciprocal linking with dictyBase-a repository of Dictyostelium genomic data. In addition, we introduce a companion application called GenBoard, an intuitive graphic user interface for data management and bioinformatics analysis. dictyExpress and GenBoard enable broad adoption of next generation sequencing based inquiries by the Dictyostelium research community. Labs without the means to undertake deep sequencing projects can mine the data available to the public. The entire information flow, from raw sequence data to hypothesis testing, can be accomplished in an efficient workspace. The software framework is generalizable and represents a useful approach for any research community. To encourage more wide usage, the backend is open-source, available for extension and further development by bioinformaticians and data scientists.

Anaerobicity Prepares Saccharomyces cerevisiae Cells for Faster Adaptation to Osmotic Shock†

PubMed Central

Krantz, Marcus; Nordlander, Bodil; Valadi, Hadi; Johansson, Mikael; Gustafsson, Lena; Hohmann, Stefan

2004-01-01

Yeast cells adapt to hyperosmotic shock by accumulating glycerol and altering expression of hundreds of genes. This transcriptional response of Saccharomyces cerevisiae to osmotic shock encompasses genes whose products are implicated in protection from oxidative damage. We addressed the question of whether osmotic shock caused oxidative stress. Osmotic shock did not result in the generation of detectable levels of reactive oxygen species (ROS). To preclude any generation of ROS, osmotic shock treatments were performed in anaerobic cultures. Global gene expression response profiles were compared by employing a novel two-dimensional cluster analysis. The transcriptional profiles following osmotic shock under anaerobic and aerobic conditions were qualitatively very similar. In particular, it appeared that expression of the oxidative stress genes was stimulated upon osmotic shock even if there was no apparent need for their function. Interestingly, cells adapted to osmotic shock much more rapidly under anaerobiosis, and the signaling as well as the transcriptional response was clearly attenuated under these conditions. This more rapid adaptation is due to an enhanced glycerol production capacity in anaerobic cells, which is caused by the need for glycerol production in redox balancing. Artificially enhanced glycerol production led to an attenuated response even under aerobic conditions. These observations demonstrate the crucial role of glycerol accumulation and turgor recovery in determining the period of osmotic shock-induced signaling and the profile of cellular adaptation to osmotic shock. PMID:15590813

Human MSC gene expression under simulated microgravity (RPM)

NASA Astrophysics Data System (ADS)

Buravkova, Ludmila; Gershovich, Pavel; Grigoriev, Anatoly

It is generally supposed that microgravity cell response is mediated by some structures of actin cytoskeleton that can be implicated in cell mechanosensitivity. Cytoskeletal reorganization in the microgravity environment can affect gene expression, which results in alterations of cell function. However the direct impact of microgravity on expression of some cytoskeletal genes and encoded proteins remains unknown. Multipotential adult mesechymal stromal cells (MSCs) are the early precursors of bone marrow that can be induced to differentiate into bone-like cells as well as to the other mesenchymal tissues. In our previous experiments we revealed cytoskele-ton alterations and reduced human MSCs growth and osteogenesis in simulated microgravity by Random Positioning Machine. The purpose of this study was to determine the impact of low gravity on F-actin organization and gene expression level of α-, β-, γ-actin, vinculin, cofilin, small GTPase RhoA, Rho kinase (ROCK) and protein expression of some adhesion molecules in cultured hMSCs. Fluorescent microscopy have shown that even 30 min of SMG results in rearrangement of F-actin and the lack of stress fibers in cultured hMSCs. Cell number with abnormal F-actin organization was increased after 6 h, 24 h and 48 h of SMG. On the other hand, after 120 hours of SMG cells displayed partial restoration of F-actin fibers in comparison with 24 h and 48 h. Similarly, near the same restoration was seen in F-actin after readaptation for 24 h in 1g environment after 24 h of SMG. However, the observed alterations in F-actin dimensional organization were accompanied by changes in related proteins gene expression. Real-time PCR revealed slight up-regulation of α-actin expression that became more signifi-cant after 48 h of SMG. Down-regulation of γ-actin was observed after 48 hours of exposure in RPM. Moreover the up-regulation of β-tubulin, cofilin and small GTPase RhoA gene expres-sion was also detected after 48 h of SMG. On the contrary, there was no significant difference between SMG and 1g control group after 120 h of exposure, except up regulation of β-tubulin and, firstly appeared down regulation of vinculin. The same results were obtained when hMSCs were exposed to 24 h readaptation after 24 h of SMG, there were no changes in expression level of all genes of interest. Thus our study has demonstrated that prolonged exposure (more than 120 h) to SMG leads to restoration of hMSC actin cytoskeleton organization. The transient changes in expression level of some genes associated with actin cytoskeleton are supposed to be one of the possible mechanisms which can contribute to first stage of precursor's cellular adaptation to microgravity.

Genome-wide investigation and expression analyses of WD40 protein family in the model plant foxtail millet (Setaria italica L.).

PubMed

Mishra, Awdhesh Kumar; Muthamilarasan, Mehanathan; Khan, Yusuf; Parida, Swarup Kumar; Prasad, Manoj

2014-01-01

WD40 proteins play a crucial role in diverse protein-protein interactions by acting as scaffolding molecules and thus assisting in the proper activity of proteins. Hence, systematic characterization and expression profiling of these WD40 genes in foxtail millet would enable us to understand the networks of WD40 proteins and their biological processes and gene functions. In the present study, a genome-wide survey was conducted and 225 potential WD40 genes were identified. Phylogenetic analysis categorized the WD40 proteins into 5 distinct sub-families (I-V). Gene Ontology annotation revealed the biological roles of the WD40 proteins along with its cellular components and molecular functions. In silico comparative mapping with sorghum, maize and rice demonstrated the orthologous relationships and chromosomal rearrangements including duplication, inversion and deletion of WD40 genes. Estimation of synonymous and non-synonymous substitution rates revealed its evolutionary significance in terms of gene-duplication and divergence. Expression profiling against abiotic stresses provided novel insights into specific and/or overlapping expression patterns of SiWD40 genes. Homology modeling enabled three-dimensional structure prediction was performed to understand the molecular functions of WD40 proteins. Although, recent findings had shown the importance of WD40 domains in acting as hubs for cellular networks during many biological processes, it has invited a lesser research attention unlike other common domains. Being a most promiscuous interactors, WD40 domains are versatile in mediating critical cellular functions and hence this genome-wide study especially in the model crop foxtail millet would serve as a blue-print for functional characterization of WD40s in millets and bioenergy grass species. In addition, the present analyses would also assist the research community in choosing the candidate WD40s for comprehensive studies towards crop improvement of millets and biofuel grasses.

Genome-Wide Investigation and Expression Analyses of WD40 Protein Family in the Model Plant Foxtail Millet (Setaria italica L.)

PubMed Central

Mishra, Awdhesh Kumar; Muthamilarasan, Mehanathan; Khan, Yusuf; Parida, Swarup Kumar; Prasad, Manoj

2014-01-01

WD40 proteins play a crucial role in diverse protein-protein interactions by acting as scaffolding molecules and thus assisting in the proper activity of proteins. Hence, systematic characterization and expression profiling of these WD40 genes in foxtail millet would enable us to understand the networks of WD40 proteins and their biological processes and gene functions. In the present study, a genome-wide survey was conducted and 225 potential WD40 genes were identified. Phylogenetic analysis categorized the WD40 proteins into 5 distinct sub-families (I–V). Gene Ontology annotation revealed the biological roles of the WD40 proteins along with its cellular components and molecular functions. In silico comparative mapping with sorghum, maize and rice demonstrated the orthologous relationships and chromosomal rearrangements including duplication, inversion and deletion of WD40 genes. Estimation of synonymous and non-synonymous substitution rates revealed its evolutionary significance in terms of gene-duplication and divergence. Expression profiling against abiotic stresses provided novel insights into specific and/or overlapping expression patterns of SiWD40 genes. Homology modeling enabled three-dimensional structure prediction was performed to understand the molecular functions of WD40 proteins. Although, recent findings had shown the importance of WD40 domains in acting as hubs for cellular networks during many biological processes, it has invited a lesser research attention unlike other common domains. Being a most promiscuous interactors, WD40 domains are versatile in mediating critical cellular functions and hence this genome-wide study especially in the model crop foxtail millet would serve as a blue-print for functional characterization of WD40s in millets and bioenergy grass species. In addition, the present analyses would also assist the research community in choosing the candidate WD40s for comprehensive studies towards crop improvement of millets and biofuel grasses. PMID:24466268

Nicotiana tabacum overexpressing γ-ECS exhibits biotic stress tolerance likely through NPR1-dependent salicylic acid-mediated pathway.

PubMed

Ghanta, Srijani; Bhattacharyya, Dipto; Sinha, Ragini; Banerjee, Anindita; Chattopadhyay, Sharmila

2011-05-01

The elaborate networks and the crosstalk of established signaling molecules like salicylic acid (SA), jasmonic acid (JA), ethylene (ET), abscisic acid (ABA), reactive oxygen species (ROS) and glutathione (GSH) play key role in plant defense response. To obtain further insight into the mechanism through which GSH is involved in this crosstalk to mitigate biotic stress, transgenic Nicotiana tabacum overexpressing Lycopersicon esculentum gamma-glutamylcysteine synthetase (LeECS) gene (NtGB lines) were generated with enhanced level of GSH in comparison with wild-type plants exhibiting resistance to pathogenesis as well. The expression levels of non-expressor of pathogenesis-related genes 1 (NPR1)-dependent genes like pathogenesis-related gene 1 (NtPR1), mitogen-activated protein kinase kinase (NtMAPKK), glutamine synthetase (NtGLS) were significantly enhanced along with NtNPR1. However, the expression levels of NPR1-independent genes like NtPR2, NtPR5 and short-chain dehydrogenase/reductase family protein (NtSDRLP) were either insignificant or were downregulated. Additionally, increase in expression of thioredoxin (NtTRXh), S-nitrosoglutathione reductase 1 (NtGSNOR1) and suppression of isochorismate synthase 1 (NtICS1) was noted. Comprehensive analysis of GSH-fed tobacco BY2 cell line in a time-dependent manner reciprocated the in planta results. Better tolerance of NtGB lines against biotrophic Pseudomonas syringae pv. tabaci was noted as compared to necrotrophic Alternaria alternata. Through two-dimensional gel electrophoresis (2-DE) and image analysis, 48 differentially expressed spots were identified and through identification as well as functional categorization, ten proteins were found to be SA-related. Collectively, our results suggest GSH to be a member in cross-communication with other signaling molecules in mitigating biotic stress likely through NPR1-dependent SA-mediated pathway.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu Xiaozhong; Hong, Sung Woo; Moreira, Estefania G.

Gonocytes exist in the neonatal testis and represent a transient population of male germ-line stem cells. It has been shown that stem cell self-renewal and progeny production is probably controlled by the neighboring differentiated cells and extracellular matrix (ECM) in vivo known as niches. Recently, we developed an in vitro three-dimensional (3D) Sertoli cell/gonocyte co-culture (SGC) model with ECM overlay, which creates an in vivo-like niche and supports germ-line stem cell functioning within a 3D environment. In this study, we applied morphological and cytotoxicity evaluations, as well as microarray-based gene expression to examine the effects of different phthalate esters (PE)more » on this model. Known in vivo male developmentally toxic PEs (DTPE) and developmentally non-toxic PEs (DNTPE) were evaluated. We observed that DTPE induced significantly greater dose-dependent morphological changes, a decrease in cell viability and an increase in cytotoxicity compared to those treated with DNTPE. Moreover, the gene expression was more greatly altered by DTPE than by DNTPE and non-supervised cluster analysis allowed the discrimination of DTPE from the DNTPE. Our systems-based GO-Quant analysis showed significant alterations in the gene pathways involved in cell cycle, phosphate transport and apoptosis regulation with DTPE but not with DNTPE treatment. Disruptions of steroidogenesis related-gene expression such as Star, Cyp19a1, Hsd17b8, and Nr4a3 were observed in the DTPE group, but not in the DNTPE group. In summary, our observation on cell viability, cytotoxicity, and microarray-based gene expression analysis induced by PEs demonstrate that our in vitro 3D-SGC system mimicked in vivo responses for PEs and suggests that the 3D-SGC system might be useful in identifying developmental reproductive toxicants.« less

Distinctive genomic signature of neural and intestinal organoids from familial Parkinson's disease patient-derived induced pluripotent stem cells.

PubMed

Son, M-Y; Sim, H; Son, Y S; Jung, K B; Lee, M-O; Oh, J-H; Chung, S-K; Jung, C-R; Kim, J

2017-12-01

The leucine-rich repeat kinase 2 (LRRK2) G2019S mutation is the most common genetic cause of Parkinson's disease (PD). There is compelling evidence that PD is not only a brain disease but also a gastrointestinal disorder; nonetheless, its pathogenesis remains unclear. We aimed to develop human neural and intestinal tissue models of PD patients harbouring an LRRK2 mutation to understand the link between LRRK2 and PD pathology by investigating the gene expression signature. We generated PD patient-specific induced pluripotent stem cells (iPSCs) carrying an LRRK2 G2019S mutation (LK2GS) and then differentiated into three-dimensional (3D) human neuroectodermal spheres (hNESs) and human intestinal organoids (hIOs). To unravel the gene and signalling networks associated with LK2GS, we analysed differentially expressed genes in the microarray data by functional clustering, gene ontology (GO) and pathway analyses. The expression profiles of LK2GS were distinct from those of wild-type controls in hNESs and hIOs. The most represented GO biological process in hNESs and hIOs was synaptic transmission, specifically synaptic vesicle trafficking, some defects of which are known to be related to PD. The results were further validated in four independent PD-specific hNESs and hIOs by microarray and qRT-PCR analysis. We provide the first evidence that LK2GS also causes significant changes in gene expression in the intestinal cells. These hNES and hIO models from the same genetic background of PD patients could be invaluable resources for understanding PD pathophysiology and for advancing the complexity of in vitro models with 3D expandable organoids. © 2017 British Neuropathological Society.

Transcriptome and Proteome Exploration to Provide a Resource for the Study of Agrocybe aegerita

PubMed Central

Jiang, Shuai; Chen, Yijie; Yin, Yalin; Pan, Yongfu; Yu, Guojun; Li, Yamu; Wong, Barry Hon Cheung; Liang, Yi; Sun, Hui

2013-01-01

Background Agrocybe aegerita, the black poplar mushroom, has been highly valued as a functional food for its medicinal and nutritional benefits. Several bioactive extracts from A. aegerita have been found to exhibit antitumor and antioxidant activities. However, limited genetic resources for A. aegerita have hindered exploration of this species. Methodology/Principal Findings To facilitate the research on A. aegerita, we established a deep survey of the transcriptome and proteome of this mushroom. We applied high-throughput sequencing technology (Illumina) to sequence A. aegerita transcriptomes from mycelium and fruiting body. The raw clean reads were de novo assembled into a total of 36,134 expressed sequences tags (ESTs) with an average length of 663 bp. These ESTs were annotated and classified according to Gene Ontology (GO), Clusters of Orthologous Groups (COG), and Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways. Gene expression profile analysis showed that 18,474 ESTs were differentially expressed, with 10,131 up-regulated in mycelium and 8,343 up-regulated in fruiting body. Putative genes involved in polysaccharide and steroid biosynthesis were identified from A. aegerita transcriptome, and these genes were differentially expressed at the two stages of A. aegerita. Based on one-dimensional gel electrophoresis (1-DGE) coupled with electrospray ionization liquid chromatography tandem MS (LC-ESI-MS/MS), we identified a total of 309 non-redundant proteins. And many metabolic enzymes involved in glycolysis were identified in the protein database. Conclusions/Significance This is the first study on transcriptome and proteome analyses of A. aegerita. The data in this study serve as a resource of A. aegerita transcripts and proteins, and offer clues to the applications of this mushroom in nutrition, pharmacy and industry. PMID:23418592

Proteomic and transcriptomic analyses of rigid and membranous cuticles and epidermis from the elytra and hindwings of the red flour beetle, Tribolium castaneum.

PubMed

Dittmer, Neal T; Hiromasa, Yasuaki; Tomich, John M; Lu, Nanyan; Beeman, Richard W; Kramer, Karl J; Kanost, Michael R

2012-01-01

The insect cuticle is a composite biomaterial made up primarily of chitin and proteins. The physical properties of the cuticle can vary greatly from hard and rigid to soft and flexible. Understanding how different cuticle types are assembled can aid in the development of novel biomimetic materials for use in medicine and technology. Toward this goal, we have taken a combined proteomics and transcriptomics approach with the red flour beetle, Tribolium castaneum, to examine the protein and gene expression profiles of the elytra and hindwings, appendages that contain rigid and soft cuticles, respectively. Two-dimensional gel electrophoresis analysis revealed distinct differences in the protein profiles between elytra and hindwings, with four highly abundant proteins dominating the elytral cuticle extract. MALDI/TOF mass spectrometry identified 19 proteins homologous to known or hypothesized cuticular proteins (CPs), including a novel low complexity protein enriched in charged residues. Microarray analysis identified 372 genes with a 10-fold or greater difference in transcript levels between elytra and hindwings. CP genes with higher expression in the elytra belonged to the Rebers and Riddiford family (CPR) type 2, or cuticular proteins of low complexity (CPLC) enriched in glycine or proline. In contrast, a majority of the CP genes with higher expression in hindwings were classified as CPR type 1, cuticular proteins analogous to peritrophins (CPAP), or members of the Tweedle family. This research shows that the elyra and hindwings, representatives of rigid and soft cuticles, have different protein and gene expression profiles for structural proteins that may influence the mechanical properties of these cuticles.

Transcriptome and proteome exploration to provide a resource for the study of Agrocybe aegerita.

PubMed

Wang, Man; Gu, Bianli; Huang, Jie; Jiang, Shuai; Chen, Yijie; Yin, Yalin; Pan, Yongfu; Yu, Guojun; Li, Yamu; Wong, Barry Hon Cheung; Liang, Yi; Sun, Hui

2013-01-01

Agrocybe aegerita, the black poplar mushroom, has been highly valued as a functional food for its medicinal and nutritional benefits. Several bioactive extracts from A. aegerita have been found to exhibit antitumor and antioxidant activities. However, limited genetic resources for A. aegerita have hindered exploration of this species. To facilitate the research on A. aegerita, we established a deep survey of the transcriptome and proteome of this mushroom. We applied high-throughput sequencing technology (Illumina) to sequence A. aegerita transcriptomes from mycelium and fruiting body. The raw clean reads were de novo assembled into a total of 36,134 expressed sequences tags (ESTs) with an average length of 663 bp. These ESTs were annotated and classified according to Gene Ontology (GO), Clusters of Orthologous Groups (COG), and Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways. Gene expression profile analysis showed that 18,474 ESTs were differentially expressed, with 10,131 up-regulated in mycelium and 8,343 up-regulated in fruiting body. Putative genes involved in polysaccharide and steroid biosynthesis were identified from A. aegerita transcriptome, and these genes were differentially expressed at the two stages of A. aegerita. Based on one-dimensional gel electrophoresis (1-DGE) coupled with electrospray ionization liquid chromatography tandem MS (LC-ESI-MS/MS), we identified a total of 309 non-redundant proteins. And many metabolic enzymes involved in glycolysis were identified in the protein database. This is the first study on transcriptome and proteome analyses of A. aegerita. The data in this study serve as a resource of A. aegerita transcripts and proteins, and offer clues to the applications of this mushroom in nutrition, pharmacy and industry.

Bowman-Birk inhibitor-like protein is secreted by sprouted pea seeds in response to induced colonization by enteropathogenic Escherichia coli.

PubMed

Anuradha, Ravi; Raveendran, Muthuraj; Babu, Subramanian

2013-11-01

The interaction between the clinical isolate of enteropathogenic Escherichia coli (EPEC) SBANU8 and pea sprouts was compared with avirulent K 12. E. coli. This was carried out by repeated co-incubation with pea sprouts for 5 days, and the protein profile of the culture supernatant was analyzed by single and two-dimensional electrophoresis. Mass spectrometry analysis led to the identification of two serine protease inhibitors including a Bowman-Birk-type protein secreted by pea sprouts in response to clinical isolate. Expression of the E. coli intimin gene involved in animal host colonization and virulence was studied by reverse transcription polymerase chain reaction. Expression of this gene was high in SBANU8 when co-incubated with pea sprouts. The present study gives baseline data on the molecular level interactions of EPEC and pea sprouts, which are needed to design the outbreak control strategies.

The role of intermediate filaments in maintaining integrity and function of intestinal epithelial cells after massive bowel resection in a rat.

PubMed

Sukhotnik, I; Shahar, Y Ben; Pollak, Y; Dorfman, T; Shefer, H Kreizman; Assi, Z E; Mor-Vaknin, N; Coran, A G

2018-02-01

Intermediate filaments (IFs) are a part of the cytoskeleton that extend throughout the cytoplasm of all cells and function in the maintenance of cell-shape by bearing tension and serving as structural components of the nuclear lamina. In normal intestine, IFs provide a tissue-specific three-dimensional scaffolding with unique context-dependent organizational features. The purpose of this study was to evaluate the role of IFs during intestinal adaptation in a rat model of short bowel syndrome (SBS). Male rats were divided into two groups: Sham rats underwent bowel transection and SBS rats underwent a 75% bowel resection. Parameters of intestinal adaptation, enterocyte proliferation and apoptosis were determined 2 weeks after operation. Illumina's Digital Gene Expression (DGE) analysis was used to determine the cytoskeleton-related gene expression profiling. IF-related genes and protein expression were determined using real-time PCR, Western blotting and immunohistochemistry. Massive small bowel resection resulted in a significant increase in enterocyte proliferation and concomitant increase in cell apoptosis. From the total number of 20,000 probes, 16 cytoskeleton-related genes were investigated. Between these genes, only myosin and tubulin levels were upregulated in SBS compared to sham animals. Between IF-related genes, desmin, vimentin and lamin levels were down-regulated and keratin and neurofilament remain unchanged. The levels of TGF-β, vimentin and desmin gene and protein were down-regulated in resected rats (vs sham animals). Two weeks following massive bowel resection in rats, the accelerated cell turnover was accompanied by a stimulated microfilaments and microtubules, and by inhibited intermediate filaments. Resistance to cell compression rather that maintenance of cell-shape by bearing tension are responsible for contraction, motility and postmitotic cell separation in a late stage of intestinal adaptation.

An Independent Filter for Gene Set Testing Based on Spectral Enrichment.

PubMed

Frost, H Robert; Li, Zhigang; Asselbergs, Folkert W; Moore, Jason H

2015-01-01

Gene set testing has become an indispensable tool for the analysis of high-dimensional genomic data. An important motivation for testing gene sets, rather than individual genomic variables, is to improve statistical power by reducing the number of tested hypotheses. Given the dramatic growth in common gene set collections, however, testing is often performed with nearly as many gene sets as underlying genomic variables. To address the challenge to statistical power posed by large gene set collections, we have developed spectral gene set filtering (SGSF), a novel technique for independent filtering of gene set collections prior to gene set testing. The SGSF method uses as a filter statistic the p-value measuring the statistical significance of the association between each gene set and the sample principal components (PCs), taking into account the significance of the associated eigenvalues. Because this filter statistic is independent of standard gene set test statistics under the null hypothesis but dependent under the alternative, the proportion of enriched gene sets is increased without impacting the type I error rate. As shown using simulated and real gene expression data, the SGSF algorithm accurately filters gene sets unrelated to the experimental outcome resulting in significantly increased gene set testing power.

Secreted HoxA3 Promotes Epidermal Proliferation and Angiogenesis in Genetically Modified Three-Dimensional Composite Skin Constructs

PubMed Central

Kuo, Jennifer H.; Cuevas, Ileana; Chen, Amy; Dunn, Ashley; Kuri, Mauricio; Boudreau, Nancy

2014-01-01

Objective: Homeobox (HOX) transcription factors coordinate gene expression in wound repair and angiogenesis. Previous studies have shown that gene transfer of HoxA3 to wounds of diabetic mice accelerates wound healing, increasing angiogenesis and keratinocyte migration. In this study, we examined whether HoxA3 can also improve angiogenesis, epidermal integrity, and viability of composite skin grafts. Approach: To determine the effects of HoxA3 on composite skin grafts, we constructed bilayered composite grafts incorporating fibroblasts engineered to constitutively secrete HoxA3. We then transplanted these composite grafts in vivo. Results: The composite grafts produced a stratified epidermal layer after seventeen days in culture and following transplantation in vivo, these grafts exhibit normal epidermal differentiation and reduced contraction compared to controls. In addition, HoxA3 grafts showed increased angiogenesis. Quantitative polymerase chain reaction (PCR) analyses of HoxA3 graft tissue reveal an increase in the downstream HoxA3 target genes MMP-14 and uPAR expression, as well as a reduction in CCL-2 and CxCl-12. Innovation: Expression of secreted HoxA3 in composite grafts represents a comprehensive approach that targets both keratinocytes and endothelial cells to promote epidermal proliferation and angiogenesis. Conclusion: Secreted HoxA3 improves angiogenesis, reduces expression of inflammatory mediators, and prolongs composite skin graft integrity. PMID:25302136

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hiser, C.; Herdies, L.; McIntosh, L.

Higher plant mitochondria posses a cyanide-resistant, hydroxamate-sensitive alternative pathway of electron transport that does not conserve energy. Aging of potato tuber slices for 24 hours leads to the development of an alternative pathway capacity. We have shown that a monoclonal antibody raised against the alternative pathway terminal oxidase of Sauromatum guttatum crossreacts with a protein of similar size in aged potato slice mitochondria. This protein was partially purified and characterized by two-dimensional gel electrophoresis, and its relative levels parallel the rise in cyanide-resistant respiration. We are using a putative clone of the S. guttatum alternative oxidase gene to isolate themore » equivalent gene from potato and to examine its expression.« less

Phospholipid and fatty acid compositions of Rhizobium leguminosarum biovar trifolii ANU843 in relation to flavone-activated pSym nod gene expression.

PubMed

Orgambide, G G; Huang, Z H; Gage, D A; Dazzo, F B

1993-11-01

The phospholipid and associated fatty acid compositions of the bacterial symbiont of clover, Rhizobium leguminosarum biovar trifolii wild-type ANU843, was analyzed by two-dimensional silica thin-layer chromatography, fast atom bombardment-mass spectrometry, flame-ionization detection gas-liquid chromatography and combined gas-liquid chromatography/mass spectrometry. The phospholipid composition included phosphatidylethanolamine (15%), N-methylphosphatidylethanolamine (47%), N,N-dimethylphosphatidylethanolamine (9%), phosphatidylglycerol (19%), cardiolipin (5%) and phosphatidylcholine (2%). Fatty acid composition included predominantly cis-11-octadecenoic acid, lower levels of cis-9-hexadecenoic acid, hexadecanoic acid, 11-methyl-11-octadecenoic acid, octadecanoic acid, 11,12-methyleneoctadecanoic acid, eicosanoic acid and traces of branched, and di- and triunsaturated fatty acids. The influence of expression of the "nodulation" genes encoding symbiotic functions on the composition of these membrane lipids was examined in wild-type cells grown with or without the flavone inducer, 4',7-dihydroxyflavone and in mutated cells lacking the entire symbiotic plasmid where these genes reside, or containing single transposon insertions in selected nodulation genes. No significant changes in phospholipid or associated fatty acid compositions were detected by the above methods of analysis.

Assessing similarity to primary tissue and cortical layer identity in induced pluripotent stem cell-derived cortical neurons through single-cell transcriptomics

PubMed Central

Handel, Adam E.; Chintawar, Satyan; Lalic, Tatjana; Whiteley, Emma; Vowles, Jane; Giustacchini, Alice; Argoud, Karene; Sopp, Paul; Nakanishi, Mahito; Bowden, Rory; Cowley, Sally; Newey, Sarah; Akerman, Colin; Ponting, Chris P.; Cader, M. Zameel

2016-01-01

Induced pluripotent stem cell (iPSC)-derived cortical neurons potentially present a powerful new model to understand corticogenesis and neurological disease. Previous work has established that differentiation protocols can produce cortical neurons, but little has been done to characterize these at cellular resolution. In particular, it is unclear to what extent in vitro two-dimensional, relatively disordered culture conditions recapitulate the development of in vivo cortical layer identity. Single-cell multiplex reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) was used to interrogate the expression of genes previously implicated in cortical layer or phenotypic identity in individual cells. Totally, 93.6% of single cells derived from iPSCs expressed genes indicative of neuronal identity. High proportions of single neurons derived from iPSCs expressed glutamatergic receptors and synaptic genes. And, 68.4% of iPSC-derived neurons expressing at least one layer marker could be assigned to a laminar identity using canonical cortical layer marker genes. We compared single-cell RNA-seq of our iPSC-derived neurons to available single-cell RNA-seq data from human fetal and adult brain and found that iPSC-derived cortical neurons closely resembled primary fetal brain cells. Unexpectedly, a subpopulation of iPSC-derived neurons co-expressed canonical fetal deep and upper cortical layer markers. However, this appeared to be concordant with data from primary cells. Our results therefore provide reassurance that iPSC-derived cortical neurons are highly similar to primary cortical neurons at the level of single cells but suggest that current layer markers, although effective, may not be able to disambiguate cortical layer identity in all cells. PMID:26740550

Combined Transcriptome and Proteome Analysis Identifies Pathways and Markers Associated with the Establishment of Rapeseed Microspore-Derived Embryo Development1[W

PubMed Central

Joosen, Ronny; Cordewener, Jan; Supena, Ence Darmo Jaya; Vorst, Oscar; Lammers, Michiel; Maliepaard, Chris; Zeilmaker, Tieme; Miki, Brian; America, Twan; Custers, Jan; Boutilier, Kim

2007-01-01

Microspore-derived embryo (MDE) cultures are used as a model system to study plant cell totipotency and as an in vitro system to study embryo development. We characterized and compared the transcriptome and proteome of rapeseed (Brassica napus) MDEs from the few-celled stage to the globular/heart stage using two MDE culture systems: conventional cultures in which MDEs initially develop as unorganized clusters that usually lack a suspensor, and a novel suspensor-bearing embryo culture system in which the embryo proper originates from the distal cell of a suspensor-like structure and undergoes the same ordered cell divisions as the zygotic embryo. Improved histodifferentiation of suspensor-bearing MDEs suggests a new role for the suspensor in driving embryo cell identity and patterning. An MDE culture cDNA array and two-dimensional gel electrophoresis and protein sequencing were used to compile global and specific expression profiles for the two types of MDE cultures. Analysis of the identities of 220 candidate embryo markers, as well as the identities of 32 sequenced embryo up-regulated protein spots, indicate general roles for protein synthesis, glycolysis, and ascorbate metabolism in the establishment of MDE development. A collection of 135 robust markers for the transition to MDE development was identified, a number of which may be coregulated at the gene and protein expression level. Comparison of the expression profiles of preglobular-stage conventional MDEs and suspensor-bearing MDEs identified genes whose differential expression may reflect improved histodifferentiation of suspensor-bearing embryos. This collection of early embryo-expressed genes and proteins serves as a starting point for future marker development and gene function studies aimed at understanding the molecular regulation of cell totipotency and early embryo development in plants. PMID:17384159

Characterization of calcineurin-dependent response element binding protein and its involvement in copper-metallothionein gene expression in Neurospora

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kumar, Kalari Satish; Ravi Kumar, B.; Siddavattam, Dayananda

2006-07-07

In continuation of our recent observations indicating the presence of a lone calcineurin-dependent response element (CDRE) in the -3730 bp upstream region of copper-induced metallothionein (CuMT) gene of Neurospora [K.S. Kumar, S. Dayananda, C. Subramanyam, Copper alone, but not oxidative stress, induces copper-metallothionein gene in Neurospora crassa, FEMS Microbiol. Lett. 242 (2005) 45-50], we isolated and characterized the CDRE-binding protein. The cloned upstream region of CuMT gene was used as the template to specifically amplify CDRE element, which was immobilized on CNBr-activated Sepharose 4B for use as the affinity matrix to purify the CDRE binding protein from nuclear extracts obtainedmore » from Neurospora cultures grown in presence of copper. Two-dimensional gel electrophoresis of the affinity purified protein revealed the presence of a single 17 kDa protein, which was identified and characterized by MALDI-TOF. Peptide mass finger printing of tryptic digests and analysis of the 17 kDa protein matched with the regulatory {beta}-subunit of calcineurin (Ca{sup 2+}-calmodulin dependent protein phosphatase). Parallel identification of nuclear localization signals in this protein by in silico analysis suggests a putative role for calcineurin in the regulation of CuMT gene expression.« less

Dynamic Imaging of Mouse Embryos and Cardiodynamics in Static Culture.

PubMed

Lopez, Andrew L; Larina, Irina V

2018-01-01

The heart is a dynamic organ that quickly undergoes morphological and mechanical changes through early embryonic development. Characterizing these early moments is important for our understanding of proper embryonic development and the treatment of heart disease. Traditionally, tomographic imaging modalities and fluorescence-based microscopy are excellent approaches to visualize structural features and gene expression patterns, respectively, and connect aberrant gene programs to pathological phenotypes. However, these approaches usually require static samples or fluorescent markers, which can limit how much information we can derive from the dynamic and mechanical changes that regulate heart development. Optical coherence tomography (OCT) is unique in this circumstance because it allows for the acquisition of three-dimensional structural and four-dimensional (3D + time) functional images of living mouse embryos without fixation or contrast reagents. In this chapter, we focus on how OCT can visualize heart morphology at different stages of development and provide cardiodynamic information to reveal mechanical properties of the developing heart.

Propagating gene expression fronts in a one-dimensional coupled system of artificial cells

NASA Astrophysics Data System (ADS)

Tayar, Alexandra M.; Karzbrun, Eyal; Noireaux, Vincent; Bar-Ziv, Roy H.

2015-12-01

Living systems employ front propagation and spatiotemporal patterns encoded in biochemical reactions for communication, self-organization and computation. Emulating such dynamics in minimal systems is important for understanding physical principles in living cells and in vitro. Here, we report a one-dimensional array of DNA compartments in a silicon chip as a coupled system of artificial cells, offering the means to implement reaction-diffusion dynamics by integrated genetic circuits and chip geometry. Using a bistable circuit we programmed a front of protein synthesis propagating in the array as a cascade of signal amplification and short-range diffusion. The front velocity is maximal at a saddle-node bifurcation from a bistable regime with travelling fronts to a monostable regime that is spatially homogeneous. Near the bifurcation the system exhibits large variability between compartments, providing a possible mechanism for population diversity. This demonstrates that on-chip integrated gene circuits are dynamical systems driving spatiotemporal patterns, cellular variability and symmetry breaking.

Simulation-based hypothesis testing of high dimensional means under covariance heterogeneity.

PubMed

Chang, Jinyuan; Zheng, Chao; Zhou, Wen-Xin; Zhou, Wen

2017-12-01

In this article, we study the problem of testing the mean vectors of high dimensional data in both one-sample and two-sample cases. The proposed testing procedures employ maximum-type statistics and the parametric bootstrap techniques to compute the critical values. Different from the existing tests that heavily rely on the structural conditions on the unknown covariance matrices, the proposed tests allow general covariance structures of the data and therefore enjoy wide scope of applicability in practice. To enhance powers of the tests against sparse alternatives, we further propose two-step procedures with a preliminary feature screening step. Theoretical properties of the proposed tests are investigated. Through extensive numerical experiments on synthetic data sets and an human acute lymphoblastic leukemia gene expression data set, we illustrate the performance of the new tests and how they may provide assistance on detecting disease-associated gene-sets. The proposed methods have been implemented in an R-package HDtest and are available on CRAN. © 2017, The International Biometric Society.

Differential expression of type X collagen in a mechanically active 3-D chondrocyte culture system: a quantitative study

PubMed Central

Yang, Xu; Vezeridis, Peter S; Nicholas, Brian; Crisco, Joseph J; Moore, Douglas C; Chen, Qian

2006-01-01

Objective Mechanical loading of cartilage influences chondrocyte metabolism and gene expression. The gene encoding type X collagen is expressed specifically by hypertrophic chondrocytes and up regulated during osteoarthritis. In this study we tested the hypothesis that the mechanical microenvironment resulting from higher levels of local strain in a three dimensional cell culture construct would lead to an increase in the expression of type X collagen mRNA by chondrocytes in those areas. Methods Hypertrophic chondrocytes were isolated from embryonic chick sterna and seeded onto rectangular Gelfoam sponges. Seeded sponges were subjected to various levels of cyclic uniaxial tensile strains at 1 Hz with the computer-controlled Bio-Stretch system. Strain distribution across the sponge was quantified by digital image analysis. After mechanical loading, sponges were cut and the end and center regions were separated according to construct strain distribution. Total RNA was extracted from the cells harvested from these regions, and real-time quantitative RT-PCR was performed to quantify mRNA levels for type X collagen and a housing-keeping gene 18S RNA. Results Chondrocytes distributed in high (9%) local strain areas produced more than two times type X collagen mRNA compared to the those under no load conditions, while chondrocytes located in low (2.5%) local strain areas had no appreciable difference in type X collagen mRNA production in comparison to non-loaded samples. Increasing local strains above 2.5%, either in the center or end regions of the sponge, resulted in increased expression of Col X mRNA by chondrocytes in that region. Conclusion These findings suggest that the threshold of chondrocyte sensitivity to inducing type X collagen mRNA production is more than 2.5% local strain, and that increased local strains above the threshold results in an increase of Col X mRNA expression. Such quantitative analysis has important implications for our understanding of mechanosensitivity of cartilage and mechanical regulation of chondrocyte gene expression. PMID:17150098

A Bootstrap Based Measure Robust to the Choice of Normalization Methods for Detecting Rhythmic Features in High Dimensional Data.

PubMed

Larriba, Yolanda; Rueda, Cristina; Fernández, Miguel A; Peddada, Shyamal D

2018-01-01

Motivation: Gene-expression data obtained from high throughput technologies are subject to various sources of noise and accordingly the raw data are pre-processed before formally analyzed. Normalization of the data is a key pre-processing step, since it removes systematic variations across arrays. There are numerous normalization methods available in the literature. Based on our experience, in the context of oscillatory systems, such as cell-cycle, circadian clock, etc., the choice of the normalization method may substantially impact the determination of a gene to be rhythmic. Thus rhythmicity of a gene can purely be an artifact of how the data were normalized. Since the determination of rhythmic genes is an important component of modern toxicological and pharmacological studies, it is important to determine truly rhythmic genes that are robust to the choice of a normalization method. Results: In this paper we introduce a rhythmicity measure and a bootstrap methodology to detect rhythmic genes in an oscillatory system. Although the proposed methodology can be used for any high-throughput gene expression data, in this paper we illustrate the proposed methodology using several publicly available circadian clock microarray gene-expression datasets. We demonstrate that the choice of normalization method has very little effect on the proposed methodology. Specifically, for any pair of normalization methods considered in this paper, the resulting values of the rhythmicity measure are highly correlated. Thus it suggests that the proposed measure is robust to the choice of a normalization method. Consequently, the rhythmicity of a gene is potentially not a mere artifact of the normalization method used. Lastly, as demonstrated in the paper, the proposed bootstrap methodology can also be used for simulating data for genes participating in an oscillatory system using a reference dataset. Availability: A user friendly code implemented in R language can be downloaded from http://www.eio.uva.es/~miguel/robustdetectionprocedure.html.

A Bootstrap Based Measure Robust to the Choice of Normalization Methods for Detecting Rhythmic Features in High Dimensional Data

PubMed Central

Larriba, Yolanda; Rueda, Cristina; Fernández, Miguel A.; Peddada, Shyamal D.

2018-01-01

Motivation: Gene-expression data obtained from high throughput technologies are subject to various sources of noise and accordingly the raw data are pre-processed before formally analyzed. Normalization of the data is a key pre-processing step, since it removes systematic variations across arrays. There are numerous normalization methods available in the literature. Based on our experience, in the context of oscillatory systems, such as cell-cycle, circadian clock, etc., the choice of the normalization method may substantially impact the determination of a gene to be rhythmic. Thus rhythmicity of a gene can purely be an artifact of how the data were normalized. Since the determination of rhythmic genes is an important component of modern toxicological and pharmacological studies, it is important to determine truly rhythmic genes that are robust to the choice of a normalization method. Results: In this paper we introduce a rhythmicity measure and a bootstrap methodology to detect rhythmic genes in an oscillatory system. Although the proposed methodology can be used for any high-throughput gene expression data, in this paper we illustrate the proposed methodology using several publicly available circadian clock microarray gene-expression datasets. We demonstrate that the choice of normalization method has very little effect on the proposed methodology. Specifically, for any pair of normalization methods considered in this paper, the resulting values of the rhythmicity measure are highly correlated. Thus it suggests that the proposed measure is robust to the choice of a normalization method. Consequently, the rhythmicity of a gene is potentially not a mere artifact of the normalization method used. Lastly, as demonstrated in the paper, the proposed bootstrap methodology can also be used for simulating data for genes participating in an oscillatory system using a reference dataset. Availability: A user friendly code implemented in R language can be downloaded from http://www.eio.uva.es/~miguel/robustdetectionprocedure.html PMID:29456555

Cohesin and related coiled-coil domain-containing complexes physically and functionally connect the dots across the genome

PubMed Central

Poon, Betty P.K

2011-01-01

Interactions between genetic regions located across the genome maintain its three-dimensional organization and function. Recent studies point to key roles for a set of coiled-coil domain-containing complexes (cohibin, cohesin, condensin and monopolin) and related factors in the regulation of DNA-DNA connections across the genome. These connections are critical to replication, recombination, gene expression as well as chromosome segregation. PMID:21822055

Cloning and characterization of two novel DNases from Streptococcus pyogenes.

PubMed

Hasegawa, Tadao; Torii, Keizo; Hashikawa, Shinnosuke; Iinuma, Yoshitsugu; Ohta, Michio

2002-06-01

The proteins in the culture supernatant (exoproteins) from Streptococcus pyogenes serotype M1 were separated by two-dimensional gel electrophoresis, and their N-terminal amino acid sequences were determined. The amino acid sequences were compared to sequences in the S. pyogenes genome database. The coding sequence showed similarity to sequences of two genes, mf2-v ( mf2 variant) and mf3, which had sequence similarity to genes encoding mitogenic factor (MF); MF has DNase activity. The recombinant genes were expressed in Escherichia coli and the proteins were synthesized. Mf2-v and Mf3 had DNase activity. The activity of Mf2-v was localized to the C-terminal half of the protein. The mf3 gene was shown to be present in most clinically isolated strains of S. pyogenes tested, and the mf2gene was detected in 20% of the isolates. The products of the mf2 and mf3 genes in clinically isolated S. pyogenes strains were thus shown to be DNases.

Fundamental limits on dynamic inference from single-cell snapshots

PubMed Central

Weinreb, Caleb; Tusi, Betsabeh K.; Socolovsky, Merav

2018-01-01

Single-cell expression profiling reveals the molecular states of individual cells with unprecedented detail. Because these methods destroy cells in the process of analysis, they cannot measure how gene expression changes over time. However, some information on dynamics is present in the data: the continuum of molecular states in the population can reflect the trajectory of a typical cell. Many methods for extracting single-cell dynamics from population data have been proposed. However, all such attempts face a common limitation: for any measured distribution of cell states, there are multiple dynamics that could give rise to it, and by extension, multiple possibilities for underlying mechanisms of gene regulation. Here, we describe the aspects of gene expression dynamics that cannot be inferred from a static snapshot alone and identify assumptions necessary to constrain a unique solution for cell dynamics from static snapshots. We translate these constraints into a practical algorithmic approach, population balance analysis (PBA), which makes use of a method from spectral graph theory to solve a class of high-dimensional differential equations. We use simulations to show the strengths and limitations of PBA, and then apply it to single-cell profiles of hematopoietic progenitor cells (HPCs). Cell state predictions from this analysis agree with HPC fate assays reported in several papers over the past two decades. By highlighting the fundamental limits on dynamic inference faced by any method, our framework provides a rigorous basis for dynamic interpretation of a gene expression continuum and clarifies best experimental designs for trajectory reconstruction from static snapshot measurements. PMID:29463712

Breast tumors from CHEK2 1100delC-mutation carriers: genomic landscape and clinical implications.

PubMed

Muranen, Taru A; Greco, Dario; Fagerholm, Rainer; Kilpivaara, Outi; Kämpjärvi, Kati; Aittomäki, Kristiina; Blomqvist, Carl; Heikkilä, Päivi; Borg, Ake; Nevanlinna, Heli

2011-09-20

Checkpoint kinase 2 (CHEK2) is a moderate penetrance breast cancer risk gene, whose truncating mutation 1100delC increases the risk about twofold. We investigated gene copy-number aberrations and gene-expression profiles that are typical for breast tumors of CHEK2 1100delC-mutation carriers. In total, 126 breast tumor tissue specimens including 32 samples from patients carrying CHEK2 1100delC were studied in array-comparative genomic hybridization (aCGH) and gene-expression (GEX) experiments. After dimensionality reduction with CGHregions R package, CHEK2 1100delC-associated regions in the aCGH data were detected by the Wilcoxon rank-sum test. The linear model was fitted to GEX data with R package limma. Genes whose expression levels were associated with CHEK2 1100delC mutation were detected by the bayesian method. We discovered four lost and three gained CHEK2 1100delC-related loci. These include losses of 1p13.3-31.3, 8p21.1-2, 8p23.1-2, and 17p12-13.1 as well as gains of 12q13.11-3, 16p13.3, and 19p13.3. Twenty-eight genes located on these regions showed differential expression between CHEK2 1100delC and other tumors, nominating them as candidates for CHEK2 1100delC-associated tumor-progression drivers. These included CLCA1 on 1p22 as well as CALCOCO1, SBEM, and LRP1 on 12q13. Altogether, 188 genes were differentially expressed between CHEK2 1100delC and other tumors. Of these, 144 had elevated and 44, reduced expression levels.Our results suggest the WNT pathway as a driver of tumorigenesis in breast tumors of CHEK2 1100delC-mutation carriers and a role for the olfactory receptor protein family in cancer progression. Differences in the expression of the 188 CHEK2 1100delC-associated genes divided breast tumor samples from three independent datasets into two groups that differed in their relapse-free survival time. We have shown that copy-number aberrations of certain genomic regions are associated with CHEK2 mutation 1100delC. On these regions, we identified potential drivers of CHEK2 1100delC-associated tumorigenesis, whose role in cancer progression is worth investigating. Furthermore, poorer survival related to the CHEK2 1100delC gene-expression signature highlights pathways that are likely to have a role in the development of metastatic disease in carriers of the CHEK2 1100delC mutation.

Breast tumors from CHEK2 1100delC-mutation carriers: genomic landscape and clinical implications

PubMed Central

2011-01-01

Introduction Checkpoint kinase 2 (CHEK2) is a moderate penetrance breast cancer risk gene, whose truncating mutation 1100delC increases the risk about twofold. We investigated gene copy-number aberrations and gene-expression profiles that are typical for breast tumors of CHEK2 1100delC-mutation carriers. Methods In total, 126 breast tumor tissue specimens including 32 samples from patients carrying CHEK2 1100delC were studied in array-comparative genomic hybridization (aCGH) and gene-expression (GEX) experiments. After dimensionality reduction with CGHregions R package, CHEK2 1100delC-associated regions in the aCGH data were detected by the Wilcoxon rank-sum test. The linear model was fitted to GEX data with R package limma. Genes whose expression levels were associated with CHEK2 1100delC mutation were detected by the bayesian method. Results We discovered four lost and three gained CHEK2 1100delC-related loci. These include losses of 1p13.3-31.3, 8p21.1-2, 8p23.1-2, and 17p12-13.1 as well as gains of 12q13.11-3, 16p13.3, and 19p13.3. Twenty-eight genes located on these regions showed differential expression between CHEK2 1100delC and other tumors, nominating them as candidates for CHEK2 1100delC-associated tumor-progression drivers. These included CLCA1 on 1p22 as well as CALCOCO1, SBEM, and LRP1 on 12q13. Altogether, 188 genes were differentially expressed between CHEK2 1100delC and other tumors. Of these, 144 had elevated and 44, reduced expression levels. Our results suggest the WNT pathway as a driver of tumorigenesis in breast tumors of CHEK2 1100delC-mutation carriers and a role for the olfactory receptor protein family in cancer progression. Differences in the expression of the 188 CHEK2 1100delC-associated genes divided breast tumor samples from three independent datasets into two groups that differed in their relapse-free survival time. Conclusions We have shown that copy-number aberrations of certain genomic regions are associated with CHEK2 mutation 1100delC. On these regions, we identified potential drivers of CHEK2 1100delC-associated tumorigenesis, whose role in cancer progression is worth investigating. Furthermore, poorer survival related to the CHEK2 1100delC gene-expression signature highlights pathways that are likely to have a role in the development of metastatic disease in carriers of the CHEK2 1100delC mutation. PMID:21542898

Global Regulatory Pathways in the Alphaproteobacteria

DOE Office of Scientific and Technical Information (OSTI.GOV)

none

A major goal for microbiologists in the twenty-first century is to develop an understanding of the microbial cell in all its complexity. In addition to understanding the function of individual gene products we need to focus on how the cell regulates gene expression at a global level to respond to different environmental parameters. Development of genomic technologies such as complete genome sequencing, proteomics, and global comparisons of mRNA expression patterns allows us to begin to address this issue. This proposal focuses on a number of phylogenetically related bacteria that are involved in environmentally important processes such as carbon sequestration andmore » bioremediation. Genome sequencing projects of a number of these bacteria have revealed the presence of a small family of regulatory genes found thus far only in the alpha-proteobacteria. These genes encode proteins that are related to the global regulatory protein RosR in Rhizobium etli, which is involved in determining nodulation competitiveness in this bacterium. Our goal is to examine the function of the proteins encoded by this gene family in several of the bacteria containing homologs to RosR. We will construct gene disruption mutations in a number of these bacteria and characterize the resulting mutant strains using two-dimensional gel electrophoresis and genetic and biochemical techniques. We will thus determine if the other proteins also function as global regulators of gene expression. Using proteomics methods we will identify the specific proteins whose expression varies depending on the presence or absence of the RosR homolog. Over fifty loci regulated by RosR have been identified in R. etli using transposon mutagenesis; this will serve as out benchmark to which we will compare the other regulons. We expect to identify genes regulated by RosR homologs in several bacterial species, including, but not limited to Rhodopseudomonas palustris and Sphingomonas aromaticivorans. In this way we will provide valuable information on gene regulation in this group of bacteria, expand our understanding of the evolution of global regulatory pathways, and develop methods for comparative regulon analysis among microbes.« less

An Optimization of Pulsed ElectroMagnetic Fields Study

NASA Technical Reports Server (NTRS)

Goodwin, Thomas J.

2006-01-01

To date, in our research we have focused on the use of normal human neuronal progenitor (NHNP) cells because of their importance in human nervous system regeneration, development and maintenance, but we have developed 2-D and 3-D bioreactors that can accommodate any cell line. In this Project, we will include the use of tissues important for physiological regeneration: Human osteoblasts or chondrocytes, and vascular cells. Our initial results with the NHNP cells were quite startling using extremely low-level electromagnetic fields (5 microtesla at 10Hz; 6mA). The low-amplitude, rapidly time-varying electromagnetic fields exert a very potent effect on the proliferation, morphology, and gene expression of the cells in culture, both in standard 2-dimensional culture plates as well as cells organized into 3-dimensional tissue-like assemblies (TLAs) in a 3D bioreactor. We have replicated our preliminary results many, many times, have analyzed the gene expression using gene arrays (followed by Luminex analysis for protein production), and have monitored cell proliferation, orientation, morphology, and glucose metabolism, and we are confident that we have a stable and reliable model to study the control of high-level cellular processes by application of low-amplitude, time varying electromagnetic fields (TVEMF) (1, 2). In additional studies at the University of Michigan, we have been able to generate functional in vitro engineered mammalian skeletal muscle, and have employed nerve-muscle co-culture techniques to promote axonal sprouting. We believe that nearly all tissues, in particular, neural, are susceptible to the influences of low-level TVEMF.

Antiestrogen Resistant Cell Lines Expressing Estrogen Receptor α Mutations Upregulate the Unfolded Protein Response and are Killed by BHPI

PubMed Central

Mao, Chengjian; Livezey, Mara; Kim, Ji Eun; Shapiro, David J.

2016-01-01

Outgrowth of metastases expressing ERα mutations Y537S and D538G is common after endocrine therapy for estrogen receptor α (ERα) positive breast cancer. The effect of replacing wild type ERα in breast cancer cells with these mutations was unclear. We used the CRISPR-Cas9 genome editing system and homology directed repair to isolate and characterize 14 T47D cell lines in which ERαY537S or ERαD538G replace one or both wild-type ERα genes. In 2-dimensional, and in quantitative anchorage-independent 3-dimensional cell culture, ERαY537S and ERαD538G cells exhibited estrogen-independent growth. A progestin further increased their already substantial proliferation in micromolar 4-hydroxytamoxifen and fulvestrant/ICI 182,780 (ICI). Our recently described ERα biomodulator, BHPI, which hyperactivates the unfolded protein response (UPR), completely blocked proliferation. In ERαY537S and ERαD538G cells, estrogen-ERα target genes were constitutively active and partially antiestrogen resistant. The UPR marker sp-XBP1 was constitutively activated in ERαY537S cells and further induced by progesterone in both cell lines. UPR-regulated genes associated with tamoxifen resistance, including the oncogenic chaperone BiP/GRP78, were upregulated. ICI displayed a greater than 2 fold reduction in its ability to induce ERαY537S and ERαD538G degradation. Progestins, UPR activation and perhaps reduced ICI-stimulated ERα degradation likely contribute to antiestrogen resistance seen in ERαY537S and ERαD538G cells. PMID:27713477

A study of metaheuristic algorithms for high dimensional feature selection on microarray data

NASA Astrophysics Data System (ADS)

Dankolo, Muhammad Nasiru; Radzi, Nor Haizan Mohamed; Sallehuddin, Roselina; Mustaffa, Noorfa Haszlinna

2017-11-01

Microarray systems enable experts to examine gene profile at molecular level using machine learning algorithms. It increases the potentials of classification and diagnosis of many diseases at gene expression level. Though, numerous difficulties may affect the efficiency of machine learning algorithms which includes vast number of genes features comprised in the original data. Many of these features may be unrelated to the intended analysis. Therefore, feature selection is necessary to be performed in the data pre-processing. Many feature selection algorithms are developed and applied on microarray which including the metaheuristic optimization algorithms. This paper discusses the application of the metaheuristics algorithms for feature selection in microarray dataset. This study reveals that, the algorithms have yield an interesting result with limited resources thereby saving computational expenses of machine learning algorithms.

Phenotype classification of single cells using SRS microscopy, RNA sequencing, and microfluidics (Conference Presentation)

NASA Astrophysics Data System (ADS)

Streets, Aaron M.; Cao, Chen; Zhang, Xiannian; Huang, Yanyi

2016-03-01

Phenotype classification of single cells reveals biological variation that is masked in ensemble measurement. This heterogeneity is found in gene and protein expression as well as in cell morphology. Many techniques are available to probe phenotypic heterogeneity at the single cell level, for example quantitative imaging and single-cell RNA sequencing, but it is difficult to perform multiple assays on the same single cell. In order to directly track correlation between morphology and gene expression at the single cell level, we developed a microfluidic platform for quantitative coherent Raman imaging and immediate RNA sequencing (RNA-Seq) of single cells. With this device we actively sort and trap cells for analysis with stimulated Raman scattering microscopy (SRS). The cells are then processed in parallel pipelines for lysis, and preparation of cDNA for high-throughput transcriptome sequencing. SRS microscopy offers three-dimensional imaging with chemical specificity for quantitative analysis of protein and lipid distribution in single cells. Meanwhile, the microfluidic platform facilitates single-cell manipulation, minimizes contamination, and furthermore, provides improved RNA-Seq detection sensitivity and measurement precision, which is necessary for differentiating biological variability from technical noise. By combining coherent Raman microscopy with RNA sequencing, we can better understand the relationship between cellular morphology and gene expression at the single-cell level.

Organogenic nodule development in hop (Humulus lupulus L.): Transcript and metabolic responses

PubMed Central

Fortes, Ana M; Santos, Filipa; Choi, Young H; Silva, Marta S; Figueiredo, Andreia; Sousa, Lisete; Pessoa, Fernando; Santos, Bartolomeu A; Sebastiana, Mónica; Palme, Klaus; Malhó, Rui; Verpoorte, Rob; Pais, Maria S

2008-01-01

Background Hop (Humulus lupulus L.) is an economically important plant forming organogenic nodules which can be used for genetic transformation and micropropagation. We are interested in the mechanisms underlying reprogramming of cells through stress and hormone treatments. Results An integrated molecular and metabolomic approach was used to investigate global gene expression and metabolic responses during development of hop's organogenic nodules. Transcript profiling using a 3,324-cDNA clone array revealed differential regulation of 133 unigenes, classified into 11 functional categories. Several pathways seem to be determinant in organogenic nodule formation, namely defense and stress response, sugar and lipid metabolism, synthesis of secondary metabolites and hormone signaling. Metabolic profiling using 1H NMR spectroscopy associated to two-dimensional techniques showed the importance of metabolites related to oxidative stress response, lipid and sugar metabolism and secondary metabolism in organogenic nodule formation. Conclusion The expression profile of genes pivotal for energy metabolism, together with metabolites profile, suggested that these morphogenic structures gain energy through a heterotrophic, transport-dependent and sugar-degrading anaerobic metabolism. Polyamines and auxins are likely to be involved in the regulation of expression of many genes related to organogenic nodule formation. These results represent substantial progress toward a better understanding of this complex developmental program and reveal novel information regarding morphogenesis in plants. PMID:18823540

Molecular characterization of alkaline protease of Bacillus amyloliquefaciens SP1 involved in biocontrol of Fusarium oxysporum.

PubMed

Guleria, Shiwani; Walia, Abhishek; Chauhan, Anjali; Shirkot, C K

2016-09-02

An alkaline protease gene was amplified from genomic DNA of Bacillus amyloliquefaciens SP1 which was involved in effective biocontrol of Fusarium oxysporum. We investigated the antagonistic capacity of protease of B. amyloliquifaciens SP1, under in vitro conditions. The 5.62 fold purified enzyme with specific activity of 607.69U/mg reported 24.14% growth inhibition of F. oxysporum. However, no antagonistic activity was found after addition of protease inhibitor i.e. PMSF (15mM) to purified enzyme. An 1149bp nucleotide sequence of protease gene encoded 382 amino acids of 43kDa and calculated isoelectric point of 9.29. Analysis of deduced amino acid sequence revealed high homology (86%) with subtilisin E of Bacillus subtilis. The B. amyloliquefaciens SP1 protease gene was expressed in Escherichiax coli BL21. The expressed protease was secreted into culture medium by E. coli and exhibited optimum activity at pH8.0 and 60°C. The most reliable three dimensional structure of alkaline protease was determined using Phyre 2 server which was validated on the basis of Ramachandran plot and ERRAT value. The expression and structure prediction of the enzyme offers potential value for commercial application in agriculture and industry. Copyright © 2016 Elsevier B.V. All rights reserved.

Stochastic resetting in backtrack recovery by RNA polymerases

NASA Astrophysics Data System (ADS)

Roldán, Édgar; Lisica, Ana; Sánchez-Taltavull, Daniel; Grill, Stephan W.

2016-06-01

Transcription is a key process in gene expression, in which RNA polymerases produce a complementary RNA copy from a DNA template. RNA polymerization is frequently interrupted by backtracking, a process in which polymerases perform a random walk along the DNA template. Recovery of polymerases from the transcriptionally inactive backtracked state is determined by a kinetic competition between one-dimensional diffusion and RNA cleavage. Here we describe backtrack recovery as a continuous-time random walk, where the time for a polymerase to recover from a backtrack of a given depth is described as a first-passage time of a random walker to reach an absorbing state. We represent RNA cleavage as a stochastic resetting process and derive exact expressions for the recovery time distributions and mean recovery times from a given initial backtrack depth for both continuous and discrete-lattice descriptions of the random walk. We show that recovery time statistics do not depend on the discreteness of the DNA lattice when the rate of one-dimensional diffusion is large compared to the rate of cleavage.

Probing RNA Native Conformational Ensembles with Structural Constraints.

PubMed

Fonseca, Rasmus; van den Bedem, Henry; Bernauer, Julie

2016-05-01

Noncoding ribonucleic acids (RNA) play a critical role in a wide variety of cellular processes, ranging from regulating gene expression to post-translational modification and protein synthesis. Their activity is modulated by highly dynamic exchanges between three-dimensional conformational substates, which are difficult to characterize experimentally and computationally. Here, we present an innovative, entirely kinematic computational procedure to efficiently explore the native ensemble of RNA molecules. Our procedure projects degrees of freedom onto a subspace of conformation space defined by distance constraints in the tertiary structure. The dimensionality reduction enables efficient exploration of conformational space. We show that the conformational distributions obtained with our method broadly sample the conformational landscape observed in NMR experiments. Compared to normal mode analysis-based exploration, our procedure diffuses faster through the experimental ensemble while also accessing conformational substates to greater precision. Our results suggest that conformational sampling with a highly reduced but fully atomistic representation of noncoding RNA expresses key features of their dynamic nature.

Toxicology studies of primycin-sulphate using a three-dimensional (3D) in vitro human liver aggregate model.

PubMed

Pénzes, Ágota; Mahmud Abdelwahab, Elhusseiny Mohamed; Rapp, Judit; Péteri, Zsanett A; Bovári-Biri, Judit; Fekete, Csaba; Miskei, György; Kvell, Krisztián; Pongrácz, Judit E

2017-11-05

Primycin-sulphate is a highly effective compound against Gram (G) positive bacteria. It has a potentially synergistic effect with vancomycin and statins which makes primycin-sulphate a potentially very effective preparation. Primycin-sulphate is currently used exclusively in topical preparations. In vitro animal hepatocyte and neuromuscular junction studies (in mice, rats, snakes, frogs) as well as in in vitro human red blood cell experiments were used to test toxicity. During these studies, the use of primycin-sulphate resulted in reduced cellular membrane integrity and modified ion channel activity. Additionally, parenteral administration of primycin-sulphate to mice, dogs, cats, rabbits and guinea pigs indicated high level of acute toxicity. The objective of this study was to reveal the cytotoxic and gene expression modifying effects of primycin-sulphate in a human system using an in vitro, three dimensional (3D) human hepatic model system. Within the 3D model, primycin-sulphate presented no acute cytotoxicity at concentrations 1μg/ml and below. However, even at low concentrations, primycin-sulphate affected gene expressions by up-regulating inflammatory cytokines (e.g., IL6), chemokines (e.g., CXCL5) and by down-regulating molecules of the lipid metabolism (e.g., peroxisome proliferator receptor (PPAR) alpha, gamma, etc). Down-regulation of PPAR alpha cannot just disrupt lipid production but can also affect cytochrome P450 metabolic enzyme (CYP) 3A4 expression, highlighting the need for extensive drug-drug interaction (DDI) studies before human oral or parenteral preparations can be developed. Copyright © 2017 Elsevier B.V. All rights reserved.

Integrative analysis of gene expression and copy number alterations using canonical correlation analysis.

PubMed

Soneson, Charlotte; Lilljebjörn, Henrik; Fioretos, Thoas; Fontes, Magnus

2010-04-15

With the rapid development of new genetic measurement methods, several types of genetic alterations can be quantified in a high-throughput manner. While the initial focus has been on investigating each data set separately, there is an increasing interest in studying the correlation structure between two or more data sets. Multivariate methods based on Canonical Correlation Analysis (CCA) have been proposed for integrating paired genetic data sets. The high dimensionality of microarray data imposes computational difficulties, which have been addressed for instance by studying the covariance structure of the data, or by reducing the number of variables prior to applying the CCA. In this work, we propose a new method for analyzing high-dimensional paired genetic data sets, which mainly emphasizes the correlation structure and still permits efficient application to very large data sets. The method is implemented by translating a regularized CCA to its dual form, where the computational complexity depends mainly on the number of samples instead of the number of variables. The optimal regularization parameters are chosen by cross-validation. We apply the regularized dual CCA, as well as a classical CCA preceded by a dimension-reducing Principal Components Analysis (PCA), to a paired data set of gene expression changes and copy number alterations in leukemia. Using the correlation-maximizing methods, regularized dual CCA and PCA+CCA, we show that without pre-selection of known disease-relevant genes, and without using information about clinical class membership, an exploratory analysis singles out two patient groups, corresponding to well-known leukemia subtypes. Furthermore, the variables showing the highest relevance to the extracted features agree with previous biological knowledge concerning copy number alterations and gene expression changes in these subtypes. Finally, the correlation-maximizing methods are shown to yield results which are more biologically interpretable than those resulting from a covariance-maximizing method, and provide different insight compared to when each variable set is studied separately using PCA. We conclude that regularized dual CCA as well as PCA+CCA are useful methods for exploratory analysis of paired genetic data sets, and can be efficiently implemented also when the number of variables is very large.

Growth Inhibition of Osteosarcoma Cell Lines in 3D Cultures: Role of Nitrosative and Oxidative Stress.

PubMed

Gorska, Magdalena; Krzywiec, Pawel Bieniasz; Kuban-Jankowska, Alicja; Zmijewski, Michal; Wozniak, Michal; Wierzbicka, Justyna; Piotrowska, Anna; Siwicka, Karolina

2016-01-01

3D cell cultures have revolutionized the understanding of cell behavior, allowing culture of cells with the possibility of resembling in vivo intercellular signaling and cell-extracellular matrix interaction. The effect of limited oxygen penetration into 3D culture of highly metastatic osteosarcoma 143B cells in terms of expression of nitro-oxidative stress markers was investigated and compared to standard 2D cell culture. Human osteosarcoma (143B cell line) cells were cultured as monolayers, in collagen and Matrigel. Cell viability, gene expression of nitro-oxidative stress markers, and vascular endothelial growth factor were determined using Trypan blue assay, quantitative polymerase chain reaction and enzyme-linked immunosorbent assay, respectively. Three-dimensional environments modify nitro-oxidative stress and influence gene expression and cell proliferation of OS 143B cells. Commercial cell lines might not constitute a good model of 3D cultures for bone tissue engineering, as they are highly sensitive to hypoxia, and hypoxic conditions can induce oxidation of the cellular environment. Copyright© 2016 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

Recurrent hotspot mutations in HRAS Q61 and PI3K-AKT pathway genes as drivers of breast adenomyoepitheliomas.

PubMed

Geyer, Felipe C; Li, Anqi; Papanastasiou, Anastasios D; Smith, Alison; Selenica, Pier; Burke, Kathleen A; Edelweiss, Marcia; Wen, Huei-Chi; Piscuoglio, Salvatore; Schultheis, Anne M; Martelotto, Luciano G; Pareja, Fresia; Kumar, Rahul; Brandes, Alissa; Fan, Dan; Basili, Thais; Da Cruz Paula, Arnaud; Lozada, John R; Blecua, Pedro; Muenst, Simone; Jungbluth, Achim A; Foschini, Maria P; Wen, Hannah Y; Brogi, Edi; Palazzo, Juan; Rubin, Brian P; Ng, Charlotte K Y; Norton, Larry; Varga, Zsuzsanna; Ellis, Ian O; Rakha, Emad A; Chandarlapaty, Sarat; Weigelt, Britta; Reis-Filho, Jorge S

2018-05-08

Adenomyoepithelioma of the breast is a rare tumor characterized by epithelial-myoepithelial differentiation, whose genetic underpinning is largely unknown. Here we show through whole-exome and targeted massively parallel sequencing analysis that whilst estrogen receptor (ER)-positive adenomyoepitheliomas display PIK3CA or AKT1 activating mutations, ER-negative adenomyoepitheliomas harbor highly recurrent codon Q61 HRAS hotspot mutations, which co-occur with PIK3CA or PIK3R1 mutations. In two- and three-dimensional cell culture models, forced expression of HRAS Q61R in non-malignant ER-negative breast epithelial cells with or without a PIK3CA H1047R somatic knock-in results in transformation and the acquisition of the cardinal features of adenomyoepitheliomas, including the expression of myoepithelial markers, a reduction in E-cadherin expression, and an increase in AKT signaling. Our results demonstrate that adenomyoepitheliomas are genetically heterogeneous, and qualify mutations in HRAS, a gene whose mutations are vanishingly rare in common-type breast cancers, as likely drivers of ER-negative adenomyoepitheliomas.

Three-Dimensional Cell Culture Systems and Their Applications in Drug Discovery and Cell-Based Biosensors

PubMed Central

Edmondson, Rasheena; Broglie, Jessica Jenkins; Adcock, Audrey F.

2014-01-01

Abstract Three-dimensional (3D) cell culture systems have gained increasing interest in drug discovery and tissue engineering due to their evident advantages in providing more physiologically relevant information and more predictive data for in vivo tests. In this review, we discuss the characteristics of 3D cell culture systems in comparison to the two-dimensional (2D) monolayer culture, focusing on cell growth conditions, cell proliferation, population, and gene and protein expression profiles. The innovations and development in 3D culture systems for drug discovery over the past 5 years are also reviewed in the article, emphasizing the cellular response to different classes of anticancer drugs, focusing particularly on similarities and differences between 3D and 2D models across the field. The progression and advancement in the application of 3D cell cultures in cell-based biosensors is another focal point of this review. PMID:24831787

Heat shock alters the expression of schizophrenia and autism candidate genes in an induced pluripotent stem cell model of the human telencephalon.

PubMed

Lin, Mingyan; Zhao, Dejian; Hrabovsky, Anastasia; Pedrosa, Erika; Zheng, Deyou; Lachman, Herbert M

2014-01-01

Schizophrenia (SZ) and autism spectrum disorders (ASD) are highly heritable neuropsychiatric disorders, although environmental factors, such as maternal immune activation (MIA), play a role as well. Cytokines mediate the effects of MIA on neurogenesis and behavior in animal models. However, MIA stimulators can also induce a febrile reaction, which could have independent effects on neurogenesis through heat shock (HS)-regulated cellular stress pathways. However, this has not been well-studied. To help understand the role of fever in MIA, we used a recently described model of human brain development in which induced pluripotent stem cells (iPSCs) differentiate into 3-dimensional neuronal aggregates that resemble a first trimester telencephalon. RNA-seq was carried out on aggregates that were heat shocked at 39°C for 24 hours, along with their control partners maintained at 37°C. 186 genes showed significant differences in expression following HS (p<0.05), including known HS-inducible genes, as expected, as well as those coding for NGFR and a number of SZ and ASD candidates, including SMARCA2, DPP10, ARNT2, AHI1 and ZNF804A. The degree to which the expression of these genes decrease or increase during HS is similar to that found in copy loss and copy gain copy number variants (CNVs), although the effects of HS are likely to be transient. The dramatic effect on the expression of some SZ and ASD genes places HS, and perhaps other cellular stressors, into a common conceptual framework with disease-causing genetic variants. The findings also suggest that some candidate genes that are assumed to have a relatively limited impact on SZ and ASD pathogenesis based on a small number of positive genetic findings, such as SMARCA2 and ARNT2, may in fact have a much more substantial role in these disorders - as targets of common environmental stressors.

Bi-Force: large-scale bicluster editing and its application to gene expression data biclustering.

PubMed

Sun, Peng; Speicher, Nora K; Röttger, Richard; Guo, Jiong; Baumbach, Jan

2014-05-01

The explosion of the biological data has dramatically reformed today's biological research. The need to integrate and analyze high-dimensional biological data on a large scale is driving the development of novel bioinformatics approaches. Biclustering, also known as 'simultaneous clustering' or 'co-clustering', has been successfully utilized to discover local patterns in gene expression data and similar biomedical data types. Here, we contribute a new heuristic: 'Bi-Force'. It is based on the weighted bicluster editing model, to perform biclustering on arbitrary sets of biological entities, given any kind of pairwise similarities. We first evaluated the power of Bi-Force to solve dedicated bicluster editing problems by comparing Bi-Force with two existing algorithms in the BiCluE software package. We then followed a biclustering evaluation protocol in a recent review paper from Eren et al. (2013) (A comparative analysis of biclustering algorithms for gene expressiondata. Brief. Bioinform., 14:279-292.) and compared Bi-Force against eight existing tools: FABIA, QUBIC, Cheng and Church, Plaid, BiMax, Spectral, xMOTIFs and ISA. To this end, a suite of synthetic datasets as well as nine large gene expression datasets from Gene Expression Omnibus were analyzed. All resulting biclusters were subsequently investigated by Gene Ontology enrichment analysis to evaluate their biological relevance. The distinct theoretical foundation of Bi-Force (bicluster editing) is more powerful than strict biclustering. We thus outperformed existing tools with Bi-Force at least when following the evaluation protocols from Eren et al. Bi-Force is implemented in Java and integrated into the open source software package of BiCluE. The software as well as all used datasets are publicly available at http://biclue.mpi-inf.mpg.de. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

The Protective Effect of Rhizoma Dioscoreae Extract against Alveolar Bone Loss in Ovariectomized Rats via Regulating Wnt and p38 MAPK Signaling

PubMed Central

Zhang, Zhiguo; Xiang, Lihua; Bai, Dong; Wang, Wenlai; Li, Yan; Pan, Jinghua; Liu, Hong; Wang, Shaojun; Xiao, Gary Guishan; Ju, Dahong

2014-01-01

Aim: The aim of this study was to evaluate the osteoprotective effect of aqueous Rhizoma Dioscoreae extract (RDE) on the alveolar bone of rats with ovariectomy-induced bone loss. Methods: Female Wistar rats were subjected to either ovariectomy or a sham operation (SHAM). The ovariectomized (OVX) rats were treated with vehicle (OVX) or RDE by oral gavage or with 17β-estradiol (E2) subcutaneously. After treatments, the bone mineral density (BMD), the three-dimensional bone architecture of the alveolar bone and the plasma biomarkers of bone turnover were analyzed to assess bone metabolism, and the histomorphometry of the alveolar bone was observed. Microarrays were used to evaluate gene expression profiles in alveolar bone from RDE-treated and OVX rats. The differential expression of genes was further analyzed using Ingenuity Pathway Analysis (IPA). The key findings were verified using real-time quantitative RT-PCR (qRT-PCR). Results: Our results showed that RDE inhibited alveolar bone loss in OVX rats. Compared to the OVX rats, the RDE-treated rats showed upregulated expression levels of 207 genes and downregulated expression levels of 176 genes in the alveolar bone. The IPA showed that several genes had the potential to code for proteins that were involved in the Wnt/β-catenin signaling pathway (Wnt7a, Fzd2, Tcf3, Spp1, Frzb, Sfrp2 and Sfrp4) and the p38 MAPK signaling pathway (Il1rn and Mapk14). Conclusion: These experiments revealed that RDE could inhibit ovariectomy-induced alveolar bone loss in rats. The mechanism of this anti-osteopenic effect in alveolar bone may be involved in the reduced abnormal bone remodeling, which is associated with the modulation of the Wnt/β-catenin and the p38 MAPK signaling pathways via gene regulation. PMID:25514564

Genome-Wide Analysis of bZIP-Encoding Genes in Maize

PubMed Central

Wei, Kaifa; Chen, Juan; Wang, Yanmei; Chen, Yanhui; Chen, Shaoxiang; Lin, Yina; Pan, Si; Zhong, Xiaojun; Xie, Daoxin

2012-01-01

In plants, basic leucine zipper (bZIP) proteins regulate numerous biological processes such as seed maturation, flower and vascular development, stress signalling and pathogen defence. We have carried out a genome-wide identification and analysis of 125 bZIP genes that exist in the maize genome, encoding 170 distinct bZIP proteins. This family can be divided into 11 groups according to the phylogenetic relationship among the maize bZIP proteins and those in Arabidopsis and rice. Six kinds of intron patterns (a–f) within the basic and hinge regions are defined. The additional conserved motifs have been identified and present the group specificity. Detailed three-dimensional structure analysis has been done to display the sequence conservation and potential distribution of the bZIP domain. Further, we predict the DNA-binding pattern and the dimerization property on the basis of the characteristic features in the basic and hinge regions and the leucine zipper, respectively, which supports our classification greatly and helps to classify 26 distinct subfamilies. The chromosome distribution and the genetic analysis reveal that 58 ZmbZIP genes are located in the segmental duplicate regions in the maize genome, suggesting that the segment chromosomal duplications contribute greatly to the expansion of the maize bZIP family. Across the 60 different developmental stages of 11 organs, three apparent clusters formed represent three kinds of different expression patterns among the ZmbZIP gene family in maize development. A similar but slightly different expression pattern of bZIPs in two inbred lines displays that 22 detected ZmbZIP genes might be involved in drought stress. Thirteen pairs and 143 pairs of ZmbZIP genes show strongly negative and positive correlations in the four distinct fungal infections, respectively, based on the expression profile and Pearson's correlation coefficient analysis. PMID:23103471

Evidence for Transcript Networks Composed of Chimeric RNAs in Human Cells

PubMed Central

Borel, Christelle; Mudge, Jonathan M.; Howald, Cédric; Foissac, Sylvain; Ucla, Catherine; Chrast, Jacqueline; Ribeca, Paolo; Martin, David; Murray, Ryan R.; Yang, Xinping; Ghamsari, Lila; Lin, Chenwei; Bell, Ian; Dumais, Erica; Drenkow, Jorg; Tress, Michael L.; Gelpí, Josep Lluís; Orozco, Modesto; Valencia, Alfonso; van Berkum, Nynke L.; Lajoie, Bryan R.; Vidal, Marc; Stamatoyannopoulos, John; Batut, Philippe; Dobin, Alex; Harrow, Jennifer; Hubbard, Tim; Dekker, Job; Frankish, Adam; Salehi-Ashtiani, Kourosh; Reymond, Alexandre; Antonarakis, Stylianos E.; Guigó, Roderic; Gingeras, Thomas R.

2012-01-01

The classic organization of a gene structure has followed the Jacob and Monod bacterial gene model proposed more than 50 years ago. Since then, empirical determinations of the complexity of the transcriptomes found in yeast to human has blurred the definition and physical boundaries of genes. Using multiple analysis approaches we have characterized individual gene boundaries mapping on human chromosomes 21 and 22. Analyses of the locations of the 5′ and 3′ transcriptional termini of 492 protein coding genes revealed that for 85% of these genes the boundaries extend beyond the current annotated termini, most often connecting with exons of transcripts from other well annotated genes. The biological and evolutionary importance of these chimeric transcripts is underscored by (1) the non-random interconnections of genes involved, (2) the greater phylogenetic depth of the genes involved in many chimeric interactions, (3) the coordination of the expression of connected genes and (4) the close in vivo and three dimensional proximity of the genomic regions being transcribed and contributing to parts of the chimeric RNAs. The non-random nature of the connection of the genes involved suggest that chimeric transcripts should not be studied in isolation, but together, as an RNA network. PMID:22238572

Blazing Signature Filter: a library for fast pairwise similarity comparisons

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Joon-Yong; Fujimoto, Grant M.; Wilson, Ryan

Identifying similarities between datasets is a fundamental task in data mining and has become an integral part of modern scientific investigation. Whether the task is to identify co-expressed genes in large-scale expression surveys or to predict combinations of gene knockouts which would elicit a similar phenotype, the underlying computational task is often a multi-dimensional similarity test. As datasets continue to grow, improvements to the efficiency, sensitivity or specificity of such computation will have broad impacts as it allows scientists to more completely explore the wealth of scientific data. A significant practical drawback of large-scale data mining is the vast majoritymore » of pairwise comparisons are unlikely to be relevant, meaning that they do not share a signature of interest. It is therefore essential to efficiently identify these unproductive comparisons as rapidly as possible and exclude them from more time-intensive similarity calculations. The Blazing Signature Filter (BSF) is a highly efficient pairwise similarity algorithm which enables extensive data mining within a reasonable amount of time. The algorithm transforms datasets into binary metrics, allowing it to utilize the computationally efficient bit operators and provide a coarse measure of similarity. As a result, the BSF can scale to high dimensionality and rapidly filter unproductive pairwise comparison. Two bioinformatics applications of the tool are presented to demonstrate the ability to scale to billions of pairwise comparisons and the usefulness of this approach.« less

Nondestructive cryomicro-CT imaging enables structural and molecular analysis of human lung tissue.

PubMed

Vasilescu, Dragoş M; Phillion, André B; Tanabe, Naoya; Kinose, Daisuke; Paige, David F; Kantrowitz, Jacob J; Liu, Gang; Liu, Hanqiao; Fishbane, Nick; Verleden, Stijn E; Vanaudenaerde, Bart M; Lenburg, Marc; Stevenson, Christopher S; Spira, Avrum; Cooper, Joel D; Hackett, Tillie-Louise; Hogg, James C

2017-01-01

Micro-computed tomography (CT) enables three-dimensional (3D) imaging of complex soft tissue structures, but current protocols used to achieve this goal preclude cellular and molecular phenotyping of the tissue. Here we describe a radiolucent cryostage that permits micro-CT imaging of unfixed frozen human lung samples at an isotropic voxel size of (11 µm) 3 under conditions where the sample is maintained frozen at -30°C during imaging. The cryostage was tested for thermal stability to maintain samples frozen up to 8 h. This report describes the methods used to choose the materials required for cryostage construction and demonstrates that whole genome mRNA integrity and expression are not compromised by exposure to micro-CT radiation and that the tissue can be used for immunohistochemistry. The new cryostage provides a novel method enabling integration of 3D tissue structure with cellular and molecular analysis to facilitate the identification of molecular determinants of disease. The described micro-CT cryostage provides a novel way to study the three-dimensional lung structure preserved without the effects of fixatives while enabling subsequent studies of the cellular matrix composition and gene expression. This approach will, for the first time, enable researchers to study structural changes of lung tissues that occur with disease and correlate them with changes in gene or protein signatures. Copyright © 2017 the American Physiological Society.

Node-Based Learning of Multiple Gaussian Graphical Models

PubMed Central

Mohan, Karthik; London, Palma; Fazel, Maryam; Witten, Daniela; Lee, Su-In

2014-01-01

We consider the problem of estimating high-dimensional Gaussian graphical models corresponding to a single set of variables under several distinct conditions. This problem is motivated by the task of recovering transcriptional regulatory networks on the basis of gene expression data containing heterogeneous samples, such as different disease states, multiple species, or different developmental stages. We assume that most aspects of the conditional dependence networks are shared, but that there are some structured differences between them. Rather than assuming that similarities and differences between networks are driven by individual edges, we take a node-based approach, which in many cases provides a more intuitive interpretation of the network differences. We consider estimation under two distinct assumptions: (1) differences between the K networks are due to individual nodes that are perturbed across conditions, or (2) similarities among the K networks are due to the presence of common hub nodes that are shared across all K networks. Using a row-column overlap norm penalty function, we formulate two convex optimization problems that correspond to these two assumptions. We solve these problems using an alternating direction method of multipliers algorithm, and we derive a set of necessary and sufficient conditions that allows us to decompose the problem into independent subproblems so that our algorithm can be scaled to high-dimensional settings. Our proposal is illustrated on synthetic data, a webpage data set, and a brain cancer gene expression data set. PMID:25309137

Mechanisms of three-dimensional growth of thyroid cells during long-term simulated microgravity

PubMed Central

Kopp, Sascha; Warnke, Elisabeth; Wehland, Markus; Aleshcheva, Ganna; Magnusson, Nils E.; Hemmersbach, Ruth; Juhl Corydon, Thomas; Bauer, Johann; Infanger, Manfred; Grimm, Daniela

2015-01-01

Three-dimensional multicellular spheroids (MCS) of human cells are important in cancer research. We investigated possible mechanisms of MCS formation of thyroid cells. Both, normal Nthy-ori 3–1 thyroid cells and the poorly differentiated follicular thyroid cancer cells FTC-133 formed MCS within 7 and 14 days of culturing on a Random Positioning Machine (RPM), while a part of the cells continued to grow adherently in each culture. The FTC-133 cancer cells formed larger and numerous MCS than the normal cells. In order to explain the different behaviour, we analyzed the gene expression of IL6, IL7, IL8, IL17, OPN, NGAL, VEGFA and enzymes associated cytoskeletal or membrane proteins (ACTB, TUBB, PFN1, CPNE1, TGM2, CD44, FLT1, FLK1, PKB, PKC, ERK1/2, Casp9, Col1A1) as well as the amount of secreted proteins (IL-6, IL-7, IL-8, IL-17, OPN, NGAL, VEGFA). Several of these components changed during RPM-exposure in each cell line. Striking differences between normal and malignant cells were observed in regards to the expression of genes of NGAL, VEGFA, OPN, IL6 and IL17 and to the secretion of VEGFA, IL-17, and IL-6. These results suggest several gravi-sensitive growth or angiogenesis factors being involved in 3D formation of thyroid cells cultured under simulated microgravity. PMID:26576504

Cloning and sequence analysis demonstrate the chromate reduction ability of a novel chromate reductase gene from Serratia sp.

PubMed

Deng, Peng; Tan, Xiaoqing; Wu, Ying; Bai, Qunhua; Jia, Yan; Xiao, Hong

2015-03-01

The ChrT gene encodes a chromate reductase enzyme which catalyzes the reduction of Cr(VI). The chromate reductase is also known as flavin mononucleotide (FMN) reductase (FMN_red). The aim of the present study was to clone the full-length ChrT DNA from Serratia sp. CQMUS2 and analyze the deduced amino acid sequence and three-dimensional structure. The putative ChrT gene fragment of Serratia sp. CQMUS2 was isolated by polymerase chain reaction (PCR), according to the known FMN_red gene sequence from Serratia sp. AS13. The flanking sequences of the ChrT gene were obtained by high efficiency TAIL-PCR, while the full-length gene of ChrT was cloned in Escherichia coli for subsequent sequencing. The nucleotide sequence of ChrT was submitted onto GenBank under the accession number, KF211434. Sequence analysis of the gene and amino acids was conducted using the Basic Local Alignment Search Tool, and open reading frame (ORF) analysis was performed using ORF Finder software. The ChrT gene was found to be an ORF of 567 bp that encodes a 188-amino acid enzyme with a calculated molecular weight of 20.4 kDa. In addition, the ChrT protein was hypothesized to be an NADPH-dependent FMN_red and a member of the flavodoxin-2 superfamily. The amino acid sequence of ChrT showed high sequence similarity to the FMN reductase genes of Klebsiella pneumonia and Raoultella ornithinolytica , which belong to the flavodoxin-2 superfamily. Furthermore, ChrT was shown to have a 85.6% similarity to the three-dimensional structure of Escherichia coli ChrR, sharing four common enzyme active sites for chromate reduction. Therefore, ChrT gene cloning and protein structure determination demonstrated the ability of the gene for chromate reduction. The results of the present study provide a basis for further studies on ChrT gene expression and protein function.

Cloning and sequence analysis demonstrate the chromate reduction ability of a novel chromate reductase gene from Serratia sp

PubMed Central

DENG, PENG; TAN, XIAOQING; WU, YING; BAI, QUNHUA; JIA, YAN; XIAO, HONG

2015-01-01

The ChrT gene encodes a chromate reductase enzyme which catalyzes the reduction of Cr(VI). The chromate reductase is also known as flavin mononucleotide (FMN) reductase (FMN_red). The aim of the present study was to clone the full-length ChrT DNA from Serratia sp. CQMUS2 and analyze the deduced amino acid sequence and three-dimensional structure. The putative ChrT gene fragment of Serratia sp. CQMUS2 was isolated by polymerase chain reaction (PCR), according to the known FMN_red gene sequence from Serratia sp. AS13. The flanking sequences of the ChrT gene were obtained by high efficiency TAIL-PCR, while the full-length gene of ChrT was cloned in Escherichia coli for subsequent sequencing. The nucleotide sequence of ChrT was submitted onto GenBank under the accession number, KF211434. Sequence analysis of the gene and amino acids was conducted using the Basic Local Alignment Search Tool, and open reading frame (ORF) analysis was performed using ORF Finder software. The ChrT gene was found to be an ORF of 567 bp that encodes a 188-amino acid enzyme with a calculated molecular weight of 20.4 kDa. In addition, the ChrT protein was hypothesized to be an NADPH-dependent FMN_red and a member of the flavodoxin-2 superfamily. The amino acid sequence of ChrT showed high sequence similarity to the FMN reductase genes of Klebsiella pneumonia and Raoultella ornithinolytica, which belong to the flavodoxin-2 superfamily. Furthermore, ChrT was shown to have a 85.6% similarity to the three-dimensional structure of Escherichia coli ChrR, sharing four common enzyme active sites for chromate reduction. Therefore, ChrT gene cloning and protein structure determination demonstrated the ability of the gene for chromate reduction. The results of the present study provide a basis for further studies on ChrT gene expression and protein function. PMID:25667630

Natural history of left ventricular mechanics in transplanted hearts: relationships with clinical variables and genetic expression profiles of allograft rejection.

PubMed

Eleid, Mackram F; Caracciolo, Giuseppe; Cho, Eun Joo; Scott, Robert L; Steidley, D Eric; Wilansky, Susan; Arabia, Francisco A; Khandheria, Bijoy K; Sengupta, Partho P

2010-10-01

The aim of this study was to explore the temporal evolution of left ventricular (LV) mechanics in relation to clinical variables and genetic expression profiles implicated in cardiac allograft function. Considerable uncertainty exists regarding the range and determinants of variability in LV systolic performance in transplanted hearts (TXH). Fifty-one patients (mean age 53 ± 12 years; 37 men) underwent serial assessment of echocardiograms, cardiac catheterization, gene expression profiles, and endomyocardial biopsy data within 2 weeks and at 3, 6, 12, and 24 months after transplantation. Two-dimensional speckle-tracking data were compared between patients with TXH and 37 controls (including 12 post-coronary artery bypass patients). Post-transplantation mortality and hospitalizations were recorded with a median follow-up period of 944 days. Global longitudinal strain (LS) and radial strain remained attenuated in patients with TXH at all time points (p < 0.001 and p = 0.005), independent of clinical rejection episodes. Failure to improve global LS at 3 months (≥ 1 SD) was associated with higher incidence of death and cardiac events (hazard ratio: 5.92; 95% confidence interval: 1.96 to 17.91; p = 0.049). Multivariate analysis revealed gene expression score as the only independent predictor of global LS (R(2) = 0.53, p = 0.005), with SEMA7A gene expression having the highest correlation with global LS (r = -0.84, p < 0.001). Speckle tracking-derived LV strains are helpful in estimating the burden of LV dysfunction in patients with TXH that evolves independent of biopsy-detected cellular rejection. Failure to improve global LS at 3 months after transplantation is associated with a higher incidence of death and cardiac events. Serial changes in LV mechanics correlate with peripheral blood gene expression profiles and may affect the clinical assessment of long-term prognosis in patients with TXH. Copyright © 2010 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Three-Dimensional Imaging of the Intracellular Fate of Plasmid DNA and Transgene Expression: ZsGreen1 and Tissue Clearing Method CUBIC Are an Optimal Combination for Multicolor Deep Imaging in Murine Tissues.

PubMed

Fumoto, Shintaro; Nishimura, Koyo; Nishida, Koyo; Kawakami, Shigeru

2016-01-01

Evaluation methods for determining the distribution of transgene expression in the body and the in vivo fate of viral and non-viral vectors are necessary for successful development of in vivo gene delivery systems. Here, we evaluated the spatial distribution of transgene expression using tissue clearing methods. After hydrodynamic injection of plasmid DNA into mice, whole tissues were subjected to tissue clearing. Tissue clearing followed by confocal laser scanning microscopy enabled evaluation of the three-dimensional distribution of transgene expression without preparation of tissue sections. Among the tested clearing methods (ClearT2, SeeDB, and CUBIC), CUBIC was the most suitable method for determining the spatial distribution of transgene expression in not only the liver but also other tissues such as the kidney and lung. In terms of the type of fluorescent protein, the observable depth for green fluorescent protein ZsGreen1 was slightly greater than that for red fluorescent protein tdTomato. We observed a depth of ~1.5 mm for the liver and 500 μm for other tissues without preparation of tissue sections. Furthermore, we succeeded in multicolor deep imaging of the intracellular fate of plasmid DNA in the murine liver. Thus, tissue clearing would be a powerful approach for determining the spatial distribution of plasmid DNA and transgene expression in various murine tissues.

Perceptual integration of kinematic components in the recognition of emotional facial expressions.

PubMed

Chiovetto, Enrico; Curio, Cristóbal; Endres, Dominik; Giese, Martin

2018-04-01

According to a long-standing hypothesis in motor control, complex body motion is organized in terms of movement primitives, reducing massively the dimensionality of the underlying control problems. For body movements, this low-dimensional organization has been convincingly demonstrated by the learning of low-dimensional representations from kinematic and EMG data. In contrast, the effective dimensionality of dynamic facial expressions is unknown, and dominant analysis approaches have been based on heuristically defined facial "action units," which reflect contributions of individual face muscles. We determined the effective dimensionality of dynamic facial expressions by learning of a low-dimensional model from 11 facial expressions. We found an amazingly low dimensionality with only two movement primitives being sufficient to simulate these dynamic expressions with high accuracy. This low dimensionality is confirmed statistically, by Bayesian model comparison of models with different numbers of primitives, and by a psychophysical experiment that demonstrates that expressions, simulated with only two primitives, are indistinguishable from natural ones. In addition, we find statistically optimal integration of the emotion information specified by these primitives in visual perception. Taken together, our results indicate that facial expressions might be controlled by a very small number of independent control units, permitting very low-dimensional parametrization of the associated facial expression.

Imaging and targeted therapy of pancreatic ductal adenocarcinoma using the theranostic sodium iodide symporter (NIS) gene

PubMed Central

Trajkovic-Arsic, Marija; Klutz, Kathrin; Braren, Rickmer; Schwaiger, Markus; Nelson, Peter J.; Ogris, Manfred; Wagner, Ernst; Siveke, Jens T.; Spitzweg, Christine

2017-01-01

The theranostic sodium iodide symporter (NIS) gene allows detailed molecular imaging of transgene expression and application of therapeutic radionuclides. As a crucial step towards clinical application, we investigated tumor specificity and transfection efficiency of epidermal growth factor receptor (EGFR)-targeted polyplexes as systemic NIS gene delivery vehicles in an advanced genetically engineered mouse model of pancreatic ductal adenocarcinoma (PDAC) that closely reflects human disease. PDAC was induced in mice by pancreas-specific activation of constitutively active KrasG12D and deletion of Trp53. We used tumor-targeted polyplexes (LPEI-PEG-GE11/NIS) based on linear polyethylenimine, shielded by polyethylene glycol and coupled with the EGFR-specific peptide ligand GE11, to target a NIS-expressing plasmid to high EGFR-expressing PDAC. In vitro iodide uptake studies in cell explants from murine EGFR-positive and EGFR-ablated PDAC lesions demonstrated high transfection efficiency and EGFR-specificity of LPEI-PEG-GE11/NIS. In vivo 123I gamma camera imaging and three-dimensional high-resolution 124I PET showed significant tumor-specific accumulation of radioiodide after systemic LPEI-PEG-GE11/NIS injection. Administration of 131I in LPEI-PEG-GE11/NIS-treated mice resulted in significantly reduced tumor growth compared to controls as determined by magnetic resonance imaging, though survival was not significantly prolonged. This study opens the exciting prospect of NIS-mediated radionuclide imaging and therapy of PDAC after systemic non-viral NIS gene delivery. PMID:28380420

Bioinformatics/biostatistics: microarray analysis.

PubMed

Eichler, Gabriel S

2012-01-01

The quantity and complexity of the molecular-level data generated in both research and clinical settings require the use of sophisticated, powerful computational interpretation techniques. It is for this reason that bioinformatic analysis of complex molecular profiling data has become a fundamental technology in the development of personalized medicine. This chapter provides a high-level overview of the field of bioinformatics and outlines several, classic bioinformatic approaches. The highlighted approaches can be aptly applied to nearly any sort of high-dimensional genomic, proteomic, or metabolomic experiments. Reviewed technologies in this chapter include traditional clustering analysis, the Gene Expression Dynamics Inspector (GEDI), GoMiner (GoMiner), Gene Set Enrichment Analysis (GSEA), and the Learner of Functional Enrichment (LeFE).

Statistical Analysis of Big Data on Pharmacogenomics

PubMed Central

Fan, Jianqing; Liu, Han

2013-01-01

This paper discusses statistical methods for estimating complex correlation structure from large pharmacogenomic datasets. We selectively review several prominent statistical methods for estimating large covariance matrix for understanding correlation structure, inverse covariance matrix for network modeling, large-scale simultaneous tests for selecting significantly differently expressed genes and proteins and genetic markers for complex diseases, and high dimensional variable selection for identifying important molecules for understanding molecule mechanisms in pharmacogenomics. Their applications to gene network estimation and biomarker selection are used to illustrate the methodological power. Several new challenges of Big data analysis, including complex data distribution, missing data, measurement error, spurious correlation, endogeneity, and the need for robust statistical methods, are also discussed. PMID:23602905

A Distinctive Cytoplasmic Tail Contributes to Low Surface Expression and Intracellular Retention of the Patr-AL MHC class I molecule1

PubMed Central

Goyos, Ana; Guethlein, Lisbeth A.; Horowitz, Amir; Hilton, Hugo G.; Gleimer, Michael; Brodsky, Frances M.; Parham, Peter

2015-01-01

Chimpanzees have orthologs of the six, fixed, functional human MHC class I genes. But in addition, the chimpanzee has a seventh functional gene, Patr-AL, which is not polymorphic but contributes substantially to population diversity by its presence on only 50% of MHC haplotypes. The ancestral AL gene emerged long before the separation of human and chimpanzee ancestors and then subsequently and specifically lost function during human evolution, but was maintained in chimpanzees. Patr-AL is an alloantigen that participates in negative and positive selection of the T-cell repertoire. The three-dimensional structure and the peptide-binding repertoire of Patr-AL and HLA-A*02 are surprisingly similar. In contrast, the expression of these two molecules is very different as shown using specific monoclonal and polyclonal antibodies made against Patr-AL. Peripheral blood cells and B cell lines express low levels of Patr-AL at the cell surface. Higher levels are seen for 221-cell transfectants expressing Patr-AL, but in these cells a large majority of Patr-AL molecules are retained in the early compartments of the secretory pathway: mainly the endoplasmic reticulum but also cis-Golgi. Replacing the cytoplasmic tail of Patr-AL with that of HLA-A*02 increased the cell-surface expression of Patr-AL substantially. Four substitutions distinguish the Patr-AL and HLA-A*02 cytoplasmic tails. Systematic mutagenesis showed that each substitution contributes changes in cell-surface expression. The combination of residues present in Patr-AL appears unique, but each individual residue is present in other primate MHC class I molecules, notably MHC-E, the most ancient of the functional human MHC class I molecules. PMID:26371256

ePlant and the 3D data display initiative: integrative systems biology on the world wide web.

PubMed

Fucile, Geoffrey; Di Biase, David; Nahal, Hardeep; La, Garon; Khodabandeh, Shokoufeh; Chen, Yani; Easley, Kante; Christendat, Dinesh; Kelley, Lawrence; Provart, Nicholas J

2011-01-10

Visualization tools for biological data are often limited in their ability to interactively integrate data at multiple scales. These computational tools are also typically limited by two-dimensional displays and programmatic implementations that require separate configurations for each of the user's computing devices and recompilation for functional expansion. Towards overcoming these limitations we have developed "ePlant" (http://bar.utoronto.ca/eplant) - a suite of open-source world wide web-based tools for the visualization of large-scale data sets from the model organism Arabidopsis thaliana. These tools display data spanning multiple biological scales on interactive three-dimensional models. Currently, ePlant consists of the following modules: a sequence conservation explorer that includes homology relationships and single nucleotide polymorphism data, a protein structure model explorer, a molecular interaction network explorer, a gene product subcellular localization explorer, and a gene expression pattern explorer. The ePlant's protein structure explorer module represents experimentally determined and theoretical structures covering >70% of the Arabidopsis proteome. The ePlant framework is accessed entirely through a web browser, and is therefore platform-independent. It can be applied to any model organism. To facilitate the development of three-dimensional displays of biological data on the world wide web we have established the "3D Data Display Initiative" (http://3ddi.org).

Irreparable complex DNA double-strand breaks induce chromosome breakage in organotypic three-dimensional human lung epithelial cell culture

PubMed Central

Asaithamby, Aroumougame; Hu, Burong; Delgado, Oliver; Ding, Liang-Hao; Story, Michael D.; Minna, John D.; Shay, Jerry W.; Chen, David J.

2011-01-01

DNA damage and consequent mutations initiate the multistep carcinogenic process. Differentiated cells have a reduced capacity to repair DNA lesions, but the biological impact of unrepaired DNA lesions in differentiated lung epithelial cells is unclear. Here, we used a novel organotypic human lung three-dimensional (3D) model to investigate the biological significance of unrepaired DNA lesions in differentiated lung epithelial cells. We showed, consistent with existing notions that the kinetics of loss of simple double-strand breaks (DSBs) were significantly reduced in organotypic 3D culture compared to kinetics of repair in two-dimensional (2D) culture. Strikingly, we found that, unlike simple DSBs, a majority of complex DNA lesions were irreparable in organotypic 3D culture. Levels of expression of multiple DNA damage repair pathway genes were significantly reduced in the organotypic 3D culture compared with those in 2D culture providing molecular evidence for the defective DNA damage repair in organotypic culture. Further, when differentiated cells with unrepaired DNA lesions re-entered the cell cycle, they manifested a spectrum of gross-chromosomal aberrations in mitosis. Our data suggest that downregulation of multiple DNA repair pathway genes in differentiated cells renders them vulnerable to DSBs, promoting genome instability that may lead to carcinogenesis. PMID:21421565

Chondrogenic Differentiation Processes in Human Bone Marrow Aspirates Seeded in Three-Dimensional Woven Poly(ε-Caprolactone) Scaffolds Enhanced by rAAV-Mediated SOX9 Gene Transfer.

PubMed

Venkatesan, Jagadeesh Kumar; Moutos, Franklin T; Rey-Rico, Ana; Estes, Bradley T; Frisch, Janina; Schmitt, Gertrud; Madry, Henning; Guilak, Farshid; Cucchiarini, Magali

2018-05-02

Combining gene therapy approaches with tissue engineering procedures is an active area of translational research for the effective treatment of articular cartilage lesions, especially to target chondrogenic progenitor cells such as those derived from the bone marrow. Here, we evaluated the effect of genetically modifying concentrated human mesenchymal stem cells from bone marrow to induce chondrogenesis by recombinant adeno-associated viral (rAAV) vector gene transfer of the sex-determining region Y-type high-mobility group box 9 (SOX9) factor upon seeding in three-dimensional (3D) woven poly(ε-caprolactone) (PCL) scaffolds that provide mechanical properties mimicking those of native articular cartilage. Prolonged, effective SOX9 expression was reported in the constructs for at least 21 days, the longest time point evaluated, leading to enhanced metabolic and chondrogenic activities relative to the control conditions (reporter lacZ gene transfer or absence of vector treatment) but without affecting the proliferative activities in the samples. The application of the rAAV SOX9 vector also prevented undesirable hypertrophic and terminal differentiation in the seeded concentrates. As bone marrow is readily accessible during surgery, such findings reveal the therapeutic potential of providing rAAV-modified marrow concentrates within 3D woven PCL scaffolds for repair of focal cartilage lesions.

Robotics and dynamic image analysis for studies of gene expression in plant tissues.

PubMed

Hernandez-Garcia, Carlos M; Chiera, Joseph M; Finer, John J

2010-05-05

Gene expression in plant tissues is typically studied by destructive extraction of compounds from plant tissues for in vitro analyses. The methods presented here utilize the green fluorescent protein (gfp) gene for continual monitoring of gene expression in the same pieces of tissues, over time. The gfp gene was placed under regulatory control of different promoters and introduced into lima bean cotyledonary tissues via particle bombardment. Cotyledons were then placed on a robotic image collection system, which consisted of a fluorescence dissecting microscope with a digital camera and a 2-dimensional robotics platform custom-designed to allow secure attachment of culture dishes. Images were collected from cotyledonary tissues every hour for 100 hours to generate expression profiles for each promoter. Each collected series of 100 images was first subjected to manual image alignment using ImageReady to make certain that GFP-expressing foci were consistently retained within selected fields of analysis. Specific regions of the series measuring 300 x 400 pixels, were then selected for further analysis to provide GFP Intensity measurements using ImageJ software. Batch images were separated into the red, green and blue channels and GFP-expressing areas were identified using the threshold feature of ImageJ. After subtracting the background fluorescence (subtraction of gray values of non-expressing pixels from every pixel) in the respective red and green channels, GFP intensity was calculated by multiplying the mean grayscale value per pixel by the total number of GFP-expressing pixels in each channel, and then adding those values for both the red and green channels. GFP Intensity values were collected for all 100 time points to yield expression profiles. Variations in GFP expression profiles resulted from differences in factors such as promoter strength, presence of a silencing suppressor, or nature of the promoter. In addition to quantification of GFP intensity, the image series were also used to generate time-lapse animations using ImageReady. Time-lapse animations revealed that the clear majority of cells displayed a relatively rapid increase in GFP expression, followed by a slow decline. Some cells occasionally displayed a sudden loss of fluorescence, which may be associated with rapid cell death. Apparent transport of GFP across the membrane and cell wall to adjacent cells was also observed. Time lapse animations provided additional information that could not otherwise be obtained using GFP Intensity profiles or single time point image collections.

A dynamic intron retention program enriched in RNA processing genes regulates gene expression during terminal erythropoiesis

DOE PAGES

Pimentel, Harold; Parra, Marilyn; Gee, Sherry L.; ...

2015-11-03

Differentiating erythroblasts execute a dynamic alternative splicing program shown here to include extensive and diverse intron retention (IR) events. Cluster analysis revealed hundreds of developmentallydynamic introns that exhibit increased IR in mature erythroblasts, and are enriched in functions related to RNA processing such as SF3B1 spliceosomal factor. Distinct, developmentally-stable IR clusters are enriched in metal-ion binding functions and include mitoferrin genes SLC25A37 and SLC25A28 that are critical for iron homeostasis. Some IR transcripts are abundant, e.g. comprising ~50% of highly-expressed SLC25A37 and SF3B1 transcripts in late erythroblasts, and thereby limiting functional mRNA levels. IR transcripts tested were predominantly nuclearlocalized. Splicemore » site strength correlated with IR among stable but not dynamic intron clusters, indicating distinct regulation of dynamically-increased IR in late erythroblasts. Retained introns were preferentially associated with alternative exons with premature termination codons (PTCs). High IR was observed in disease-causing genes including SF3B1 and the RNA binding protein FUS. Comparative studies demonstrated that the intron retention program in erythroblasts shares features with other tissues but ultimately is unique to erythropoiesis. Finally, we conclude that IR is a multi-dimensional set of processes that post-transcriptionally regulate diverse gene groups during normal erythropoiesis, misregulation of which could be responsible for human disease.« less

Partial kinetoplast-mitochondrial gene organization and expression in the respiratory deficient plant trypanosomatid Phytomonas serpens.

PubMed

Maslov, D A; Nawathean, P; Scheel, J

1999-04-30

In plant-dwelling trypanosomatids from the genus Phytomonas, mitochondrial functions, such as cytochrome mediated respiration, ATP production and Krebs cycle, are missing, and cell energetics is based on the glycolysis. Using Blue Native/Tricine-SDS two-dimensional gel electrophoretic analysis, we observed that mitochondrial respiratory Complexes III (cytochrome bc1) and IV (cytochrome c oxidase) were absent in Phytomonas serpens; however, Complex V (ATPase) was present. A deletion of the genes for cytochrome c oxidase subunit III (COIII) and apocytochrome b (Cyb) was identified within the 6234 bp sequenced region of the 31 kb maxicircle kinetoplast DNA. Genes, found in this region, include 12S and 9S ribosomal RNAs, subunits 7, 8 and 9 of NADH dehydrogenase (ND7, ND8 and ND9) and subunit 6 of ATPase (A6 or MURF4), as well as the genes (MURF1, MURF5 and G3) with unknown function. Most genes are actively transcribed and some mRNAs are edited. Fully edited mRNAs for A6 and G3 were abundant, while edited ND7 transcripts were rare, and only partially edited and pre-edited transcripts for ND8 were detected. The data show that the mitochondrial genome of P. serpens is functional, although its functions may be limited to expressing the ATPase and, possibly, NADH dehydrogenase complexes.

A dynamic intron retention program enriched in RNA processing genes regulates gene expression during terminal erythropoiesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pimentel, Harold; Parra, Marilyn; Gee, Sherry L.

Differentiating erythroblasts execute a dynamic alternative splicing program shown here to include extensive and diverse intron retention (IR) events. Cluster analysis revealed hundreds of developmentallydynamic introns that exhibit increased IR in mature erythroblasts, and are enriched in functions related to RNA processing such as SF3B1 spliceosomal factor. Distinct, developmentally-stable IR clusters are enriched in metal-ion binding functions and include mitoferrin genes SLC25A37 and SLC25A28 that are critical for iron homeostasis. Some IR transcripts are abundant, e.g. comprising ~50% of highly-expressed SLC25A37 and SF3B1 transcripts in late erythroblasts, and thereby limiting functional mRNA levels. IR transcripts tested were predominantly nuclearlocalized. Splicemore » site strength correlated with IR among stable but not dynamic intron clusters, indicating distinct regulation of dynamically-increased IR in late erythroblasts. Retained introns were preferentially associated with alternative exons with premature termination codons (PTCs). High IR was observed in disease-causing genes including SF3B1 and the RNA binding protein FUS. Comparative studies demonstrated that the intron retention program in erythroblasts shares features with other tissues but ultimately is unique to erythropoiesis. Finally, we conclude that IR is a multi-dimensional set of processes that post-transcriptionally regulate diverse gene groups during normal erythropoiesis, misregulation of which could be responsible for human disease.« less

Cyclic mechanical stretch contributes to network development of osteocyte-like cells with morphological change and autophagy promotion but without preferential cell alignment in rat.

PubMed

Inaba, Nao; Kuroshima, Shinichiro; Uto, Yusuke; Sasaki, Muneteru; Sawase, Takashi

2017-09-01

Osteocytes play important roles in controlling bone quality as well as preferential alignment of biological apatite c -axis/collagen fibers. However, the relationship between osteocytes and mechanical stress remains unclear due to the difficulty of three-dimensional (3D) culture of osteocytes in vitro . The aim of this study was to investigate the effect of cyclic mechanical stretch on 3D-cultured osteocyte-like cells. Osteocyte-like cells were established using rat calvarial osteoblasts cultured in a 3D culture system. Cyclic mechanical stretch (8% amplitude at a rate of 2 cycles min -1 ) was applied for 24, 48 and 96 consecutive hours. Morphology, cell number and preferential cell alignment were evaluated. Apoptosis- and autophagy-related gene expression levels were measured using quantitative PCR. 3D-cultured osteoblasts became osteocyte-like cells that expressed osteocyte-specific genes such as Dmp1 , Cx43 , Sost , Fgf23 and RANKL , with morphological changes similar to osteocytes. Cell number was significantly decreased in a time-dependent manner under non-loaded conditions, whereas cyclic mechanical stretch significantly prevented decreased cell numbers with increased expression of anti-apoptosis-related genes. Moreover, cyclic mechanical stretch significantly decreased cell size and ellipticity with increased expression of autophagy-related genes, LC3b and atg7 . Interestingly, preferential cell alignment did not occur, irrespective of mechanical stretch. These findings suggest that an anti-apoptotic effect contributes to network development of osteocyte-like cells under loaded condition. Spherical change of osteocyte-like cells induced by mechanical stretch may be associated with autophagy upregulation. Preferential alignment of osteocytes induced by mechanical load in vivo may be partially predetermined before osteoblasts differentiate into osteocytes and embed into bone matrix.

Identification and Characterization of Two Temperature-Induced Surface-Associated Proteins of Streptococcus suis with High Homologies to Members of the Arginine Deiminase System of Streptococcus pyogenes

PubMed Central

Winterhoff, Nora; Goethe, Ralph; Gruening, Petra; Rohde, Manfred; Kalisz, Henryk; Smith, Hilde E.; Valentin-Weigand, Peter

2002-01-01

The present study was performed to identify stress-induced putative virulence proteins of Streptococcus suis. For this, protein expression patterns of streptococci grown at 32, 37, and 42°C were compared by one- and two-dimensional gel electrophoresis. Temperature shifts from 32 and 37 to 42°C induced expression of two cell wall-associated proteins with apparent molecular masses of approximately 47 and 53 kDa. Amino-terminal sequence analysis of the two proteins indicated homologies of the 47-kDa protein with an ornithine carbamoyltransferase (OCT) from Streptococcus pyogenes and of the 53-kDa protein with the streptococcal acid glycoprotein (SAGP) from S. pyogenes, an arginine deiminase (AD) recently proposed as a putative virulence factor. Cloning and sequencing the genes encoding the putative OCT and AD of S. suis, octS and adiS, respectively, revealed that they had 81.2 (octS) and 80.2% (adiS) identity with the respective genes of S. pyogenes. Both genes belong to the AD system, also found in other bacteria. Southern hybridization analysis demonstrated the presence of the adiS gene in all 42 serotype 2 and 9 S. suis strains tested. In 9 of these 42 strains, selected randomly, we confirmed expression of the AdiS protein, homologous to SAGP, by immunoblot analysis using a specific antiserum against the SAGP of S. pyogenes. In all strains AD activity was detected. Furthermore, by immunoelectron microscopy using the anti-S. pyogenes SAGP antiserum we were able to demonstrate that the AdiS protein is expressed on the streptococcal surface in association with the capsular polysaccharides but is not coexpressed with them. PMID:12446626

Homologue gene of bile acid transporters ntcp, asbt, and ost-alpha in rainbow trout Oncorhynchus mykiss: tissue expression, effect of fasting, and response to bile acid administration.

PubMed

Murashita, Koji; Yoshiura, Yasutoshi; Chisada, Shin-Ichi; Furuita, Hirofumi; Sugita, Tsuyoshi; Matsunari, Hiroyuki; Iwashita, Yasuro; Yamamoto, Takeshi

2014-04-01

Bile acid transporters belonging to the SLC10A protein family, Na+ taurocholate cotransporting polypeptide (NTCP or SLC10A1), apical sodium-dependent bile salt transporter (ASBT or SLC10A2), and organic solute transporter alpha (Ost-alpha) have been known to play critical roles in the enterohepatic circulation of bile acids in mammals. In this study, ntcp, asbt, and ost-alpha-1/-2 cDNA were cloned, their tissue distributions were characterized, and the effects of fasting and bile acid administration on their expression were examined in rainbow trout Oncorhynchus mykiss. The structural characteristics of Ntcp, Asbt, and Ost-alpha were well conserved in trout, and three-dimensional structure analysis showed that Ntcp and Asbt were similar to each other. Tissue distribution analysis revealed that trout asbt was primarily expressed in the hindgut, while ntcp expression occurred in the brain, and ost-alpha-1/-2 was mainly expressed in the liver or ovary. Although asbt and ost-alpha-1 mRNA levels in the gut increased in response to fasting for 4 days, ost-alpha-1 expression in the liver decreased. Similarly, bile acid administration increased asbt and ost-alpha-1 expression levels in the gut, while those of ntcp and ost-alpha-2 in the liver decreased. These results suggested that the genes asbt, ntcp, and ost-alpha are involved in bile acid transport in rainbow trout.

CSAX: Characterizing Systematic Anomalies in eXpression Data.

PubMed

Noto, Keith; Majidi, Saeed; Edlow, Andrea G; Wick, Heather C; Bianchi, Diana W; Slonim, Donna K

2015-05-01

Methods for translating gene expression signatures into clinically relevant information have typically relied upon having many samples from patients with similar molecular phenotypes. Here, we address the question of what can be done when it is relatively easy to obtain healthy patient samples, but when abnormalities corresponding to disease states may be rare and one-of-a-kind. The associated computational challenge, anomaly detection, is a well-studied machine-learning problem. However, due to the dimensionality and variability of expression data, existing methods based on feature space analysis or individual anomalously expressed genes are insufficient. We present a novel approach, CSAX, that identifies pathways in an individual sample in which the normal expression relationships are disrupted. To evaluate our approach, we have compiled and released a compendium of public expression data sets, reformulated to create a test bed for anomaly detection. We demonstrate the accuracy of CSAX on the data sets in our compendium, compare it to other leading methods, and show that CSAX aids in both identifying anomalies and explaining their underlying biology. We describe an approach to characterizing the difficulty of specific expression anomaly detection tasks. We then illustrate CSAX's value in two developmental case studies. Confirming prior hypotheses, CSAX highlights disruption of platelet activation pathways in a neonate with retinopathy of prematurity and identifies, for the first time, dysregulated oxidative stress response in second trimester amniotic fluid of fetuses with obese mothers. Our approach provides an important step toward identification of individual disease patterns in the era of precision medicine.

In vivo imaging of inducible tyrosinase gene expression with an ultrasound array-based photoacoustic system

NASA Astrophysics Data System (ADS)

Harrison, Tyler; Paproski, Robert J.; Zemp, Roger J.

2012-02-01

Tyrosinase, a key enzyme in the production of melanin, has shown promise as a reporter of genetic activity. While green fluorescent protein has been used extensively in this capacity, it is limited in its ability to provide information deep in tissue at a reasonable resolution. As melanin is a strong absorber of light, it is possible to image gene expression using tyrosinase with photoacoustic imaging technologies, resulting in excellent resolutions at multiple-centimeter depths. While our previous work has focused on creating and imaging MCF-7 cells with doxycycline-controlled tyrosinase expression, we have now established the viability of these cells in a murine model. Using an array-based photoacoustic imaging system with 5 MHz center frequency, we capture interleaved ultrasound and photoacoustic images of tyrosinase-expressing MCF-7 tumors both in a tissue mimicking phantom, and in vivo. Images of both the tyrosinase-expressing tumor and a control tumor are presented as both coregistered ultrasound-photoacoustic B-scan images and 3-dimensional photoacoustic volumes created by mechanically scanning the transducer. We find that the tyrosinase-expressing tumor is visible with a signal level 12dB greater than that of the control tumor in vivo. Phantom studies with excised tumors show that the tyrosinase-expressing tumor is visible at depths in excess of 2cm, and have suggested that our imaging system is sensitive to a transfection rate of less than 1%.

Molecular cloning, characterization and expression profiles of multiple leptin genes and a leptin receptor gene in orange-spotted grouper (Epinephelus coioides).

PubMed

Zhang, Huixian; Chen, Huapu; Zhang, Yong; Li, Shuisheng; Lu, Danqi; Zhang, Haifa; Meng, Zining; Liu, Xiaochun; Lin, Haoran

2013-01-15

Leptin plays key roles in body weight regulation, energy metabolism, food intake, reproduction and immunity in mammals. However, its function in teleosts is still unclear. In the present study, two leptin genes (gLepA and gLepB) and one leptin receptor gene (gLepR) were cloned and characterized in orange-spotted grouper (Epinephelus coioides). The cDNAs of gLepA and gLepB were 671 bp and 684 bp in length, encoding for proteins of 161 amino acid (aa) and 158 aa, respectively. The three-dimensional (3D) structures modeling of gLepA and gLepB showed strong conservation of tertiary structure with that of other vertebrates. The total length of gLepR cDNA was 4242 bp, encoding a protein of 1169 aa which contained all functionally important domains conserved among vertebrate LEPR. Tissue distribution analysis showed that gLepA was highly expressed in cerebellum, liver and ovary, while gLepB mRNA abundantly in the brain regions, as well as in the ovary with some extend. The gLepR was mainly expressed in kidney, head kidney and most of brain regions. Analysis of expression profiles of gLep and gLepR genes during the embryonic stages showed that high expression of gLepR was observed in the brain vesicle stage, while neither gLepA nor gLepB mRNA was detected during different embryonic stages. Finally, fasting and refeeding experiments were carried out to investigate the possible function of leptin genes in food intake and energy metabolism, and the results showed that a significant increase of gLepA expression in the liver was induced by food deprivation in both short-term (7 days) and long-term (3 weeks) fasting and gLepA mRNA upregulation was eliminated after refeeding, while gLepB wasn't detected in the liver of grouper during fasting. No significant differences in hypothalamic leptin and leptin receptor expression were found during short-term fasting and refeeding. Hepatic expression of gLepA mRNA increased significantly 9h after a single meal. These results suggested gLepA, other than gLepB, functioned in the regulation of energy metabolism and food intake in this Perciform fish. Copyright © 2012 Elsevier Inc. All rights reserved.

CRISPR Knockout of the HuR Gene Causes a Xenograft Lethal Phenotype.

PubMed

Lal, Shruti; Cheung, Edwin C; Zarei, Mahsa; Preet, Ranjan; Chand, Saswati N; Mambelli-Lisboa, Nicole C; Romeo, Carmella; Stout, Matthew C; Londin, Eric; Goetz, Austin; Lowder, Cinthya Y; Nevler, Avinoam; Yeo, Charles J; Campbell, Paul M; Winter, Jordan M; Dixon, Dan A; Brody, Jonathan R

2017-06-01

Pancreatic ductal adenocarcinoma (PDA) is the third leading cause of cancer-related deaths in the United States, whereas colorectal cancer is the third most common cancer. The RNA-binding protein HuR (ELAVL1) supports a pro-oncogenic network in gastrointestinal (GI) cancer cells through enhanced HuR expression. Using a publically available database, HuR expression levels were determined to be increased in primary PDA and colorectal cancer tumor cohorts as compared with normal pancreas and colon tissues, respectively. CRISPR/Cas9 technology was successfully used to delete the HuR gene in both PDA (MIA PaCa-2 and Hs 766T) and colorectal cancer (HCT116) cell lines. HuR deficiency has a mild phenotype, in vitro , as HuR-deficient MIA PaCa-2 (MIA.HuR-KO (-/-) ) cells had increased apoptosis when compared with isogenic wild-type (MIA.HuR-WT (+/+) ) cells. Using this isogenic system, mRNAs were identified that specifically bound to HuR and were required for transforming a two-dimensional culture into three dimensional (i.e., organoids). Importantly, HuR-deficient MIA PaCa-2 and Hs 766T cells were unable to engraft tumors in vivo compared with control HuR-proficient cells, demonstrating a unique xenograft lethal phenotype. Although not as a dramatic phenotype, CRISPR knockout HuR HCT116 colon cancer cells (HCT.HuR-KO (-/-) ) showed significantly reduced in vivo tumor growth compared with controls (HCT.HuR-WT (+/+) ). Finally, HuR deletion affects KRAS activity and controls a subset of pro-oncogenic genes. Implications: The work reported here supports the notion that targeting HuR is a promising therapeutic strategy to treat GI malignancies. Mol Cancer Res; 15(6); 696-707. ©2017 AACR . ©2017 American Association for Cancer Research.

Mutation of the murC and murB Genes Impairs Heterocyst Differentiation in Anabaena sp. Strain PCC 7120

PubMed Central

Videau, Patrick; Rivers, Orion S.; Ushijima, Blake; Oshiro, Reid T.; Kim, Min Joo; Philmus, Benjamin

2016-01-01

ABSTRACT To stabilize cellular integrity in the face of environmental perturbations, most bacteria, including cyanobacteria, synthesize and maintain a strong, flexible, three-dimensional peptidoglycan lattice. Anabaena sp. strain PCC 7120 is a filamentous cyanobacterium capable of differentiating morphologically distinct nitrogen-fixing heterocyst cells in a periodic pattern. While heterocyst development has been shown to require proper peptidoglycan remodeling, the role of peptidoglycan synthesis has remained unclear. Here we report the identification of two peptidoglycan synthesis genes, murC (alr5065) and murB (alr5066), as required for heterocyst development. The murC and murB genes are predicted to encode a UDP-N-acetylmuramate:l-alanine ligase and a UDP-N-acetylenolpyruvoylglucosamine reductase, respectively, and we confirm enzymatic function through complementation of Escherichia coli strains deficient for these enzymes. Cells depleted of either murC or murB expression failed to differentiate heterocysts under normally inducing conditions and displayed decreased filament integrity. To identify the stage(s) of development affected by murC or murB depletion, the spatial distribution of expression of the patterning marker gene, patS, was examined. Whereas murB depletion did not affect the pattern of patS expression, murC depletion led to aberrant expression of patS in all cells of the filament. Finally, expression of gfp controlled by the region of DNA immediately upstream of murC was enriched in differentiating cells and was repressed by the transcription factor NtcA. Collectively, the data in this work provide evidence for a direct link between peptidoglycan synthesis and the maintenance of a biological pattern in a multicellular organism. IMPORTANCE Multicellular organisms that differentiate specialized cells must regulate morphological changes such that both cellular integrity and the dissemination of developmental signals are preserved. Here we show that the multicellular bacterium Anabaena, which differentiates a periodic pattern of specialized heterocyst cells, requires peptidoglycan synthesis by the murine ligase genes murC (alr5065) and murB (alr5066) for maintenance of patterned gene expression, filament integrity, and overall development. This work highlights the significant influence that intracellular structure and intercellular connections can have on the execution of a developmental program. PMID:26811320

Mutation of the murC and murB Genes Impairs Heterocyst Differentiation in Anabaena sp. Strain PCC 7120.

PubMed

Videau, Patrick; Rivers, Orion S; Ushijima, Blake; Oshiro, Reid T; Kim, Min Joo; Philmus, Benjamin; Cozy, Loralyn M

2016-04-01

To stabilize cellular integrity in the face of environmental perturbations, most bacteria, including cyanobacteria, synthesize and maintain a strong, flexible, three-dimensional peptidoglycan lattice. Anabaena sp. strain PCC 7120 is a filamentous cyanobacterium capable of differentiating morphologically distinct nitrogen-fixing heterocyst cells in a periodic pattern. While heterocyst development has been shown to require proper peptidoglycan remodeling, the role of peptidoglycan synthesis has remained unclear. Here we report the identification of two peptidoglycan synthesis genes, murC (alr5065) and murB (alr5066), as required for heterocyst development. The murC and murB genes are predicted to encode a UDP-N-acetylmuramate:L-alanine ligase and a UDP-N-acetylenolpyruvoylglucosamine reductase, respectively, and we confirm enzymatic function through complementation of Escherichia coli strains deficient for these enzymes. Cells depleted of either murC or murB expression failed to differentiate heterocysts under normally inducing conditions and displayed decreased filament integrity. To identify the stage(s) of development affected by murC or murB depletion, the spatial distribution of expression of the patterning marker gene, patS, was examined. Whereas murB depletion did not affect the pattern of patS expression, murC depletion led to aberrant expression of patS in all cells of the filament. Finally, expression of gfp controlled by the region of DNA immediately upstream of murC was enriched in differentiating cells and was repressed by the transcription factor NtcA. Collectively, the data in this work provide evidence for a direct link between peptidoglycan synthesis and the maintenance of a biological pattern in a multicellular organism. Multicellular organisms that differentiate specialized cells must regulate morphological changes such that both cellular integrity and the dissemination of developmental signals are preserved. Here we show that the multicellular bacterium Anabaena, which differentiates a periodic pattern of specialized heterocyst cells, requires peptidoglycan synthesis by the murine ligase genes murC (alr5065) and murB (alr5066) for maintenance of patterned gene expression, filament integrity, and overall development. This work highlights the significant influence that intracellular structure and intercellular connections can have on the execution of a developmental program. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Comparative transcriptional and translational analysis of leptospiral outer membrane protein expression in response to temperature.

PubMed

Lo, Miranda; Cordwell, Stuart J; Bulach, Dieter M; Adler, Ben

2009-12-08

Leptospirosis is a global zoonosis affecting millions of people annually. Transcriptional changes in response to temperature were previously investigated using microarrays to identify genes potentially expressed upon host entry. Past studies found that various leptospiral outer membrane proteins are differentially expressed at different temperatures. However, our microarray studies highlighted a divergence between protein abundance and transcript levels for some proteins. Given the abundance of post-transcriptional expression control mechanisms, this finding highlighted the importance of global protein analysis systems. To complement our previous transcription study, we evaluated differences in the proteins of the leptospiral outer membrane fraction in response to temperature upshift. Outer membrane protein-enriched fractions from Leptospira interrogans grown at 30 degrees C or overnight upshift to 37 degrees C were isolated and the relative abundance of each protein was determined by iTRAQ analysis coupled with two-dimensional liquid chromatography and tandem mass spectrometry (2-DLC/MS-MS). We identified 1026 proteins with 99% confidence; 27 and 66 were present at elevated and reduced abundance respectively. Protein abundance changes were compared with transcriptional differences determined from the microarray studies. While there was some correlation between the microarray and iTRAQ data, a subset of genes that showed no differential expression by microarray was found to encode temperature-regulated proteins. This set of genes is of particular interest as it is likely that regulation of their expression occurs post-transcriptionally, providing an opportunity to develop hypotheses about the molecular dynamics of the outer membrane of Leptospira in response to changing environments. This is the first study to compare transcriptional and translational responses to temperature shift in L. interrogans. The results thus provide an insight into the mechanisms used by L. interrogans to adapt to conditions encountered in the host and to cause disease. Our results suggest down-regulation of protein expression in response to temperature, and decreased expression of outer membrane proteins may facilitate minimal interaction with host immune mechanisms.

CellTree: an R/bioconductor package to infer the hierarchical structure of cell populations from single-cell RNA-seq data.

PubMed

duVerle, David A; Yotsukura, Sohiya; Nomura, Seitaro; Aburatani, Hiroyuki; Tsuda, Koji

2016-09-13

Single-cell RNA sequencing is fast becoming one the standard method for gene expression measurement, providing unique insights into cellular processes. A number of methods, based on general dimensionality reduction techniques, have been suggested to help infer and visualise the underlying structure of cell populations from single-cell expression levels, yet their models generally lack proper biological grounding and struggle at identifying complex differentiation paths. Here we introduce cellTree: an R/Bioconductor package that uses a novel statistical approach, based on document analysis techniques, to produce tree structures outlining the hierarchical relationship between single-cell samples, while identifying latent groups of genes that can provide biological insights. With cellTree, we provide experimentalists with an easy-to-use tool, based on statistically and biologically-sound algorithms, to efficiently explore and visualise single-cell RNA data. The cellTree package is publicly available in the online Bionconductor repository at: http://bioconductor.org/packages/cellTree/ .

Comprehensive analysis of the dynamic structure of nuclear localization signals.

PubMed

Yamagishi, Ryosuke; Okuyama, Takahide; Oba, Shuntaro; Shimada, Jiro; Chaen, Shigeru; Kaneko, Hiroki

2015-12-01

Most transcription and epigenetic factors in eukaryotic cells have nuclear localization signals (NLSs) and are transported to the nucleus by nuclear transport proteins. Understanding the features of NLSs and the mechanisms of nuclear transport might help understand gene expression regulation, somatic cell reprogramming, thus leading to the treatment of diseases associated with abnormal gene expression. Although many studies analyzed the amino acid sequence of NLSs, few studies investigated their three-dimensional structure. Therefore, we conducted a statistical investigation of the dynamic structure of NLSs by extracting the conformation of these sequences from proteins examined by X-ray crystallography and using a quantity defined as conformational determination rate (a ratio between the number of amino acids determining the conformation and the number of all amino acids included in a certain region). We found that determining the conformation of NLSs is more difficult than determining the conformation of other regions and that NLSs may tend to form more heteropolymers than monomers. Therefore, these findings strongly suggest that NLSs are intrinsically disordered regions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Ren; Boudreau, Aaron; Bissell, Mina J

Mammary gland development, functional differentiation, and homeostasis are orchestrated and sustained by a balance of biochemical and biophysical cues from the organ's microenvironment. The three-dimensional microenvironment of the mammary gland, predominantly 'encoded' by a collaboration between the extracellular matrix (ECM), hormones, and growth factors, sends signals from ECM receptors through the cytoskeletal intracellular matrix to nuclear and chromatin structures resulting in gene expression; the ECM in turn is regulated and remodeled by signals from the nucleus. In this chapter, we discuss how coordinated ECM deposition and remodeling is necessary for mammary gland development, how the ECM provides structural and biochemicalmore » cues necessary for tissue-specific function, and the role of the cytoskeleton in mediating the extra - to intracellular dialogue occurring between the nucleus and the microenvironment. When operating normally, the cytoskeletal-mediated dynamic and reciprocal integration of tissue architecture and function directs mammary gland development, tissue polarity, and ultimately, tissue-specific gene expression. Cancer occurs when these dynamic interactions go awry for an extended time.« less

Proteomic characterization of a mouse model of familial Danish dementia.

PubMed

Vitale, Monica; Renzone, Giovanni; Matsuda, Shuji; Scaloni, Andrea; D'Adamio, Luciano; Zambrano, Nicola

2012-01-01

A dominant mutation in the ITM2B/BRI2 gene causes familial Danish dementia (FDD) in humans. To model FDD in animal systems, a knock-in approach was recently implemented in mice expressing a wild-type and mutant allele, which bears the FDD-associated mutation. Since these FDD(KI) mice show behavioural alterations and impaired synaptic function, we characterized their synaptosomal proteome via two-dimensional differential in-gel electrophoresis. After identification by nanoliquid chromatography coupled to electrospray-linear ion trap tandem mass spectrometry, the differentially expressed proteins were classified according to their gene ontology descriptions and their predicted functional interactions. The Dlg4/Psd95 scaffold protein and additional signalling proteins, including protein phosphatases, were revealed by STRING analysis as potential players in the altered synaptic function of FDD(KI) mice. Immunoblotting analysis finally demonstrated the actual downregulation of the synaptosomal scaffold protein Dlg4/Psd95 and of the dual-specificity phosphatase Dusp3 in the synaptosomes of FDD(KI) mice.

Proteomic Characterization of a Mouse Model of Familial Danish Dementia

PubMed Central

Vitale, Monica; Renzone, Giovanni; Matsuda, Shuji; Scaloni, Andrea; D'Adamio, Luciano; Zambrano, Nicola

2012-01-01

A dominant mutation in the ITM2B/BRI2 gene causes familial Danish dementia (FDD) in humans. To model FDD in animal systems, a knock-in approach was recently implemented in mice expressing a wild-type and mutant allele, which bears the FDD-associated mutation. Since these FDDKI mice show behavioural alterations and impaired synaptic function, we characterized their synaptosomal proteome via two-dimensional differential in-gel electrophoresis. After identification by nanoliquid chromatography coupled to electrospray-linear ion trap tandem mass spectrometry, the differentially expressed proteins were classified according to their gene ontology descriptions and their predicted functional interactions. The Dlg4/Psd95 scaffold protein and additional signalling proteins, including protein phosphatases, were revealed by STRING analysis as potential players in the altered synaptic function of FDDKI mice. Immunoblotting analysis finally demonstrated the actual downregulation of the synaptosomal scaffold protein Dlg4/Psd95 and of the dual-specificity phosphatase Dusp3 in the synaptosomes of FDDKI mice. PMID:22619496

Epigenetic reprogramming governs EcSOD expression during human mammary epithelial cell differentiation, tumorigenesis and metastasis

PubMed Central

Teoh-Fitzgerald, ML; Fitzgerald, MP; Zhong, W; Askeland, RW; Domann, FE

2013-01-01

Expression of the antioxidant enzyme EcSOD in normal human mammary epithelial cells was not recognized until recently. Although expression of EcSOD was not detectable in non-malignant human mammary epithelial cells (HMEC) cultured in conventional two-dimensional (2D) culture conditions, EcSOD protein expression was observed in normal human breast tissues, suggesting that the 2D-cultured condition induces a repressive status of EcSOD gene expression in HMEC. With the use of laminin-enriched extracellular matrix (lrECM), we were able to detect expression of EcSOD when HMEC formed polarized acinar structures in a 3D-culture condition. Repression of the EcSOD-gene expression was again seen when the HMEC acini were sub-cultured as a monolayer, implying that lrECM-induced acinar morphogenesis is essential in EcSOD-gene activation. We have further shown the involvement of DNA methylation in regulating EcSOD expression in HMEC under these cell culture conditions. EcSOD mRNA expression was strongly induced in the 2D-cultured HMEC after treatment with a DNA methyltransferase inhibitor. In addition, epigenetic analyses showed a decrease in the degree of CpG methylation in the EcSOD promoter in the 3D versus 2D-cultured HMEC. More importantly, >80% of clinical mammary adenocarcinoma samples showed significantly decreased EcSOD mRNA and protein expression levels compared with normal mammary tissues and there is an inverse correlation between the expression levels of EcSOD and the clinical stages of breast cancer. Combined bisulfite restriction analysis analysis of some of the tumors also revealed an association of DNA methylation with the loss of EcSOD expression in vivo. Furthermore, overexpression of EcSOD inhibited breast cancer metastasis in both the experimental lung metastasis model and the syngeneic mouse model. This study suggests that epigenetic silencing of EcSOD may contribute to mammary tumorigenesis and that restoring the extracellular superoxide scavenging activity could be an effective strategy for breast cancer treatment. PMID:23318435

A hitchhiker's guide to the human Hsp70 family

PubMed Central

Tavaria, Michael; Gabriele, Tim; Kola, Ismail; Anderson, Robin L.

1996-01-01

The human Hsp70 family encompasses at least 11 genes which encode a group of highly related proteins. These proteins include both cognate and highly inducible members, at least some of which act as molecular chaperones. The location of cognate Hsp70s within all the major subcellular compartments is an indication of the importance of these proteins. The expression of several inducible Hsp70 genes is also an indication of the importance of these proteins in the stres response. The existence of multiple genes and protein isoforms has created confusion in the identification and naming of particular family members. We have compiled, from the literature, a list of genes and genetic loci and produced a two-dimensional protein map of the known human Hsp70 family members. This will enable researchers in the field to quickly and reliably identify human Hsp70s. We have also devised a more rational nomenclature for these genes and gene products which, subject to general acceptance, could be extended to Hsp70 families from other species. PMID:9222585

SoFoCles: feature filtering for microarray classification based on gene ontology.

PubMed

Papachristoudis, Georgios; Diplaris, Sotiris; Mitkas, Pericles A

2010-02-01

Marker gene selection has been an important research topic in the classification analysis of gene expression data. Current methods try to reduce the "curse of dimensionality" by using statistical intra-feature set calculations, or classifiers that are based on the given dataset. In this paper, we present SoFoCles, an interactive tool that enables semantic feature filtering in microarray classification problems with the use of external, well-defined knowledge retrieved from the Gene Ontology. The notion of semantic similarity is used to derive genes that are involved in the same biological path during the microarray experiment, by enriching a feature set that has been initially produced with legacy methods. Among its other functionalities, SoFoCles offers a large repository of semantic similarity methods that are used in order to derive feature sets and marker genes. The structure and functionality of the tool are discussed in detail, as well as its ability to improve classification accuracy. Through experimental evaluation, SoFoCles is shown to outperform other classification schemes in terms of classification accuracy in two real datasets using different semantic similarity computation approaches.

Shared regulatory sites are abundant in the human genome and shed light on genome evolution and disease pleiotropy.

PubMed

Tong, Pin; Monahan, Jack; Prendergast, James G D

2017-03-01

Large-scale gene expression datasets are providing an increasing understanding of the location of cis-eQTLs in the human genome and their role in disease. However, little is currently known regarding the extent of regulatory site-sharing between genes. This is despite it having potentially wide-ranging implications, from the determination of the way in which genetic variants may shape multiple phenotypes to the understanding of the evolution of human gene order. By first identifying the location of non-redundant cis-eQTLs, we show that regulatory site-sharing is a relatively common phenomenon in the human genome, with over 10% of non-redundant regulatory variants linked to the expression of multiple nearby genes. We show that these shared, local regulatory sites are linked to high levels of chromatin looping between the regulatory sites and their associated genes. In addition, these co-regulated gene modules are found to be strongly conserved across mammalian species, suggesting that shared regulatory sites have played an important role in shaping human gene order. The association of these shared cis-eQTLs with multiple genes means they also appear to be unusually important in understanding the genetics of human phenotypes and pleiotropy, with shared regulatory sites more often linked to multiple human phenotypes than other regulatory variants. This study shows that regulatory site-sharing is likely an underappreciated aspect of gene regulation and has important implications for the understanding of various biological phenomena, including how the two and three dimensional structures of the genome have been shaped and the potential causes of disease pleiotropy outside coding regions.

Comparative analysis of 3D culture methods on human HepG2 cells.

PubMed

Luckert, Claudia; Schulz, Christina; Lehmann, Nadja; Thomas, Maria; Hofmann, Ute; Hammad, Seddik; Hengstler, Jan G; Braeuning, Albert; Lampen, Alfonso; Hessel, Stefanie

2017-01-01

Human primary hepatocytes represent a gold standard in in vitro liver research. Due to their low availability and high costs alternative liver cell models with comparable morphological and biochemical characteristics have come into focus. The human hepatocarcinoma cell line HepG2 is often used as a liver model for toxicity studies. However, under two-dimensional (2D) cultivation conditions the expression of xenobiotic-metabolizing enzymes and typical liver markers such as albumin is very low. Cultivation for 21 days in a three-dimensional (3D) Matrigel culture system has been reported to strongly increase the metabolic competence of HepG2 cells. In our present study we further compared HepG2 cell cultivation in three different 3D systems: collagen, Matrigel and Alvetex culture. Cell morphology, albumin secretion, cytochrome P450 monooxygenase enzyme activities, as well as gene expression of xenobiotic-metabolizing and liver-specific enzymes were analyzed after 3, 7, 14, and 21 days of cultivation. Our results show that the previously reported increase of metabolic competence of HepG2 cells is not primarily the result of 3D culture but a consequence of the duration of cultivation. HepG2 cells grown for 21 days in 2D monolayer exhibit comparable biochemical characteristics, CYP activities and gene expression patterns as all 3D culture systems used in our study. However, CYP activities did not reach the level of HepaRG cells. In conclusion, the increase of metabolic competence of the hepatocarcinoma cell line HepG2 is not due to 3D cultivation but rather a result of prolonged cultivation time.

The potential of 3-dimensional construct engineered from poly(lactic-co-glycolic acid)/fibrin hybrid scaffold seeded with bone marrow mesenchymal stem cells for in vitro cartilage tissue engineering.

PubMed

Abdul Rahman, Rozlin; Mohamad Sukri, Norhamiza; Md Nazir, Noorhidayah; Ahmad Radzi, Muhammad Aa'zamuddin; Zulkifly, Ahmad Hafiz; Che Ahmad, Aminudin; Hashi, Abdurezak Abdulahi; Abdul Rahman, Suzanah; Sha'ban, Munirah

2015-08-01

Articular cartilage is well known for its simple uniqueness of avascular and aneural structure that has limited capacity to heal itself when injured. The use of three dimensional construct in tissue engineering holds great potential in regenerating cartilage defects. This study evaluated the in vitro cartilaginous tissue formation using rabbit's bone marrow mesenchymal stem cells (BMSCs)-seeded onto poly(lactic-co-glycolic acid) PLGA/fibrin and PLGA scaffolds. The in vitro cartilaginous engineered constructs were evaluated by gross inspection, histology, cell proliferation, gene expression and sulphated glycosaminoglycan (sGAG) production at week 1, 2 and 3. After 3 weeks of culture, the PLGA/fibrin construct demonstrated gross features similar to the native tissue with smooth, firm and glistening appearance, superior histoarchitectural and better cartilaginous extracellular matrix compound in concert with the positive glycosaminoglycan accumulation on Alcian blue. Significantly higher cell proliferation in PLGA/fibrin construct was noted at day-7, day-14 and day-21 (p<0.05 respectively). Both constructs expressed the accumulation of collagen type II, collagen type IX, aggrecan and sox9, showed down-regulation of collagen type I as well as produced relative sGAG content with PLGA/fibrin construct exhibited better gene expression in all profiles and showed significantly higher relative sGAG content at each time point (p<0.05). This study suggested that with optimum in vitro manipulation, PLGA/fibrin when seeded with pluripotent non-committed BMSCs has the capability to differentiate into chondrogenic lineage and may serve as a prospective construct to be developed as functional tissue engineered cartilage. Copyright © 2015 Elsevier Ltd. All rights reserved.

Three-dimensional development of tensile pre-strained annulus fibrosus cells for tissue regeneration: An in-vitro study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chuah, Yon Jin; Lee, Wu Chean; Wong, Hee Kit

Prior research has investigated the immediate response after application of tensile strain on annulus fibrosus (AF) cells for the past decade. Although mechanical strain can produce either catabolic or anabolic consequences to the cell monolayer, little is known on how to translate these findings into further tissue engineering applications. Till to date, the application and effect of tensile pre-strained cells to construct a three-dimensional (3D) AF tissue remains unknown. This study aims to investigate the effect of tensile pre-strained exposure of 1 to 24 h on the development of AF pellet culture for 3 weeks. Equibiaxial cyclic tensile strain wasmore » applied on AF monolayer cells over a period of 24 h, which was subsequently developed into a cell pellet. Investigation on cellular proliferation, phenotypic gene expression, and histological changes revealed that tensile pre-strain for 24 h had significant and lasting effect on the AF tissue development, with enhanced cell proliferation, and up-regulation of collagen type I, II, and aggrecan expression. Our results demonstrated the regenerative ability of AF cell pellets subjected to 24 h tensile pre-straining. Knowledge on the effects of tensile pre-strain exposure is necessary to optimize AF development for tissue reconstruction. Moreover, the tensile pre-strained cells may further be utilized in either cell therapy to treat mild disc degeneration disease, or the development of a disc construct for total disc replacement. - Highlights: • Establishment of tensile pre-strained cell line population for annulus development. • Tensile strain limits collagen gene expression declination in monolayer culture. • Tensile pre-strained cells up-regulate their matrix protein in 3D pellet culture.« less

Analysis of type II diabetes mellitus adipose-derived stem cells for tissue engineering applications

PubMed Central

Minteer, Danielle Marie; Young, Matthew T; Lin, Yen-Chih; Over, Patrick J; Rubin, J Peter; Gerlach, Jorg C

2015-01-01

To address the functionality of diabetic adipose-derived stem cells in tissue engineering applications, adipose-derived stem cells isolated from patients with and without type II diabetes mellitus were cultured in bioreactor culture systems. The adipose-derived stem cells were differentiated into adipocytes and maintained as functional adipocytes. The bioreactor system utilizes a hollow fiber–based technology for three-dimensional perfusion of tissues in vitro, creating a model in which long-term culture of adipocytes is feasible, and providing a potential tool useful for drug discovery. Daily metabolic activity of the adipose-derived stem cells was analyzed within the medium recirculating throughout the bioreactor system. At experiment termination, tissues were extracted from bioreactors for immunohistological analyses in addition to gene and protein expression. Type II diabetic adipose-derived stem cells did not exhibit significantly different glucose consumption compared to adipose-derived stem cells from patients without type II diabetes (p > 0.05, N = 3). Expression of mature adipocyte genes was not significantly different between diabetic/non-diabetic groups (p > 0.05, N = 3). Protein expression of adipose tissue grown within all bioreactors was verified by Western blotting.The results from this small-scale study reveal adipose-derived stem cells from patients with type II diabetes when removed from diabetic environments behave metabolically similar to the same cells of non-diabetic patients when cultured in a three-dimensional perfusion bioreactor, suggesting that glucose transport across the adipocyte cell membrane, the hindrance of which being characteristic of type II diabetes, is dependent on environment. The presented observation describes a tissue-engineered tool for long-term cell culture and, following future adjustments to the culture environment and increased sample sizes, potentially for anti-diabetic drug testing. PMID:26090087

A two-step hierarchical hypothesis set testing framework, with applications to gene expression data on ordered categories

PubMed Central

2014-01-01

Background In complex large-scale experiments, in addition to simultaneously considering a large number of features, multiple hypotheses are often being tested for each feature. This leads to a problem of multi-dimensional multiple testing. For example, in gene expression studies over ordered categories (such as time-course or dose-response experiments), interest is often in testing differential expression across several categories for each gene. In this paper, we consider a framework for testing multiple sets of hypothesis, which can be applied to a wide range of problems. Results We adopt the concept of the overall false discovery rate (OFDR) for controlling false discoveries on the hypothesis set level. Based on an existing procedure for identifying differentially expressed gene sets, we discuss a general two-step hierarchical hypothesis set testing procedure, which controls the overall false discovery rate under independence across hypothesis sets. In addition, we discuss the concept of the mixed-directional false discovery rate (mdFDR), and extend the general procedure to enable directional decisions for two-sided alternatives. We applied the framework to the case of microarray time-course/dose-response experiments, and proposed three procedures for testing differential expression and making multiple directional decisions for each gene. Simulation studies confirm the control of the OFDR and mdFDR by the proposed procedures under independence and positive correlations across genes. Simulation results also show that two of our new procedures achieve higher power than previous methods. Finally, the proposed methodology is applied to a microarray dose-response study, to identify 17 β-estradiol sensitive genes in breast cancer cells that are induced at low concentrations. Conclusions The framework we discuss provides a platform for multiple testing procedures covering situations involving two (or potentially more) sources of multiplicity. The framework is easy to use and adaptable to various practical settings that frequently occur in large-scale experiments. Procedures generated from the framework are shown to maintain control of the OFDR and mdFDR, quantities that are especially relevant in the case of multiple hypothesis set testing. The procedures work well in both simulations and real datasets, and are shown to have better power than existing methods. PMID:24731138

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Nan; Guan, Ju; Ferrer, Jean-Luc

Two benzenoid esters, methyl salicylate (MeSA) and methyl benzoate (MeBA), were detected from insect-damaged rice plants. By correlating metabolite production with gene expression analysis, five candidate genes encoding putative carboxyl methyltransferases were identified. Enzymatic assays with Escherichia coli-expressed recombinant proteins demonstrated that only one of the five candidates, OsBSMT1, has salicylic acid (SA) methyltransferase (SAMT) and benzoic acid (BA) methyltransferase (BAMT) activities for producing MeSA and MeBA, respectively. Whereas OsBSMT1 is phylogenetically relatively distant from dicot SAMTs, the three-dimensional structure of OsBSMT1, which was determined using homology-based structural modeling, is highly similar to those of characterized SAMTs. Analyses of OsBSMT1more » expression in wild-type rice plants under various stress conditions indicate that the jasmonic acid (JA) signaling pathway plays a critical role in regulating the production and emission of MeSA in rice. Further analysis using transgenic rice plants overexpressing NH1, a key component of the SA signaling pathway in rice, suggests that the SA signaling pathway also plays an important role in governing OsBSMT1 expression and emission of its products, probably through a crosstalk with the JA signaling pathway. The role of the volatile products of OsBSMT1, MeSA and MeBA, in rice defense against insect herbivory is discussed.« less

JOINT AND INDIVIDUAL VARIATION EXPLAINED (JIVE) FOR INTEGRATED ANALYSIS OF MULTIPLE DATA TYPES.

PubMed

Lock, Eric F; Hoadley, Katherine A; Marron, J S; Nobel, Andrew B

2013-03-01

Research in several fields now requires the analysis of datasets in which multiple high-dimensional types of data are available for a common set of objects. In particular, The Cancer Genome Atlas (TCGA) includes data from several diverse genomic technologies on the same cancerous tumor samples. In this paper we introduce Joint and Individual Variation Explained (JIVE), a general decomposition of variation for the integrated analysis of such datasets. The decomposition consists of three terms: a low-rank approximation capturing joint variation across data types, low-rank approximations for structured variation individual to each data type, and residual noise. JIVE quantifies the amount of joint variation between data types, reduces the dimensionality of the data, and provides new directions for the visual exploration of joint and individual structure. The proposed method represents an extension of Principal Component Analysis and has clear advantages over popular two-block methods such as Canonical Correlation Analysis and Partial Least Squares. A JIVE analysis of gene expression and miRNA data on Glioblastoma Multiforme tumor samples reveals gene-miRNA associations and provides better characterization of tumor types.

Three-dimensional cell organization leads to almost immediate HRE activity as demonstrated by molecular imaging of MG-63 spheroids using two-photon excitation microscopy.

PubMed

Indovina, Paola; Collini, Maddalena; Chirico, Giuseppe; Santini, Maria Teresa

2007-02-20

Hypoxia through HRE (hypoxia-responsive element) activity in MG-63 human osteosarcoma cells grown in monolayer and as very small, three-dimensional tumor spheroids was investigated using molecular imaging techniques. MG-63 cells were stably transfected with a vector constructed with multiple copies of the HRE sequence of the human vascular endothelial growth factor (VEGF) gene and with the enhanced green fluorescent protein (EGFP) coding sequence. During hypoxia when HIF-1alpha (hypoxia-inducible factor-1alpha) is stabilized, the binding of HIF-1 to the HRE sequences of the vector allows the transcription of EGFP and the appearance of fluorescence. Transfected monolayer cells were characterized by flow cytometric analysis in response to various hypoxic conditions and HIF-1alpha expression in these cells was assessed by Western blotting. Two-photon excitation (TPE) microscopy was then used to examine both MG-63-transfected monolayer cells and spheroids at 2 and 5 days of growth in normoxic conditions. Monolayer cells reveal almost no fluorescence, whereas even very small spheroids (<100 microm) after 2 days of growth contain regions of high fluorescence. For the first time in the literature, at least to our knowledge, it is demonstrated, using highly sensitive and non-perturbing molecular imaging techniques, that three-dimensional cell organization leads to almost immediate HRE activation. This activation of the HRE sequences, which control a wide variety of genes, suggests that monolayer cells and spheroids of the MG-63 cell line have different genes activated and thus diverse functional activities.

MicroRNA857 Is Involved in the Regulation of Secondary Growth of Vascular Tissues in Arabidopsis1

PubMed Central

Zhao, Yuanyuan; Lin, Sen; Qiu, Zongbo; Cao, Dechang; Wen, Jialong; Deng, Xin; Wang, Xiaohua; Lin, Jinxing; Li, Xiaojuan

2015-01-01

MicroRNAs (miRNAs) are endogenous small RNAs that repress target gene expression posttranscriptionally, and are critically involved in various developmental processes and responses to environmental stresses in eukaryotes. MiRNA857 is not widely distributed in plants and is encoded by a single gene, AtMIR857, in Arabidopsis (Arabidopsis thaliana). The functions of miR857 and its mechanisms in regulating plant growth and development are still unclear. Here, by means of genetic analysis coupled with cytological studies, we investigated the expression pattern and regulation mechanism of miR857 and its biological functions in Arabidopsis development. We found that miR857 regulates its target gene, Arabidopsis LACCASE7, at the transcriptional level, thereby reducing laccase activity. Using stimulated Raman scattering and x-ray microtomography three-dimensional analyses, we showed that miR857 was involved in the regulation of lignin content and consequently morphogenesis of the secondary xylem. In addition, miR857 was activated by SQUAMOSA PROMOTER BINDING PROTEIN-LIKE7 in response to low copper conditions. Collectively, these findings demonstrate the role of miR857 in the regulation of secondary growth of vascular tissues in Arabidopsis and reveal a unique control mechanism for secondary growth based on the miR857 expression in response to copper deficiency. PMID:26511915

Dissecting the Calcium-Induced Differentiation of Human Primary Keratinocytes Stem Cells by Integrative and Structural Network Analyses

PubMed Central

Toufighi, Kiana; Yang, Jae-Seong; Luis, Nuno Miguel; Aznar Benitah, Salvador; Lehner, Ben; Serrano, Luis; Kiel, Christina

2015-01-01

The molecular details underlying the time-dependent assembly of protein complexes in cellular networks, such as those that occur during differentiation, are largely unexplored. Focusing on the calcium-induced differentiation of primary human keratinocytes as a model system for a major cellular reorganization process, we look at the expression of genes whose products are involved in manually-annotated protein complexes. Clustering analyses revealed only moderate co-expression of functionally related proteins during differentiation. However, when we looked at protein complexes, we found that the majority (55%) are composed of non-dynamic and dynamic gene products (‘di-chromatic’), 19% are non-dynamic, and 26% only dynamic. Considering three-dimensional protein structures to predict steric interactions, we found that proteins encoded by dynamic genes frequently interact with a common non-dynamic protein in a mutually exclusive fashion. This suggests that during differentiation, complex assemblies may also change through variation in the abundance of proteins that compete for binding to common proteins as found in some cases for paralogous proteins. Considering the example of the TNF-α/NFκB signaling complex, we suggest that the same core complex can guide signals into diverse context-specific outputs by addition of time specific expressed subunits, while keeping other cellular functions constant. Thus, our analysis provides evidence that complex assembly with stable core components and competition could contribute to cell differentiation. PMID:25946651

β1 integrin is a crucial regulator of pancreatic β-cell expansion

PubMed Central

Diaferia, Giuseppe R.; Jimenez-Caliani, Antonio J.; Ranjitkar, Prerana; Yang, Wendy; Hardiman, Gary; Rhodes, Christopher J.; Crisa, Laura; Cirulli, Vincenzo

2013-01-01

Development of the endocrine compartment of the pancreas, as represented by the islets of Langerhans, occurs through a series of highly regulated events encompassing branching of the pancreatic epithelium, delamination and differentiation of islet progenitors from ductal domains, followed by expansion and three-dimensional organization into islet clusters. Cellular interactions with the extracellular matrix (ECM) mediated by receptors of the integrin family are postulated to regulate key functions in these processes. Yet, specific events regulated by these receptors in the developing pancreas remain unknown. Here, we show that ablation of the β1 integrin gene in developing pancreatic β-cells reduces their ability to expand during embryonic life, during the first week of postnatal life, and thereafter. Mice lacking β1 integrin in insulin-producing cells exhibit a dramatic reduction of the number of β-cells to only ∼18% of wild-type levels. Despite the significant reduction in β-cell mass, these mutant mice are not diabetic. A thorough phenotypic analysis of β-cells lacking β1 integrin revealed a normal expression repertoire of β-cell markers, normal architectural organization within islet clusters, and a normal ultrastructure. Global gene expression analysis revealed that ablation of this ECM receptor in β-cells inhibits the expression of genes regulating cell cycle progression. Collectively, our results demonstrate that β1 integrin receptors function as crucial positive regulators of β-cell expansion. PMID:23863477

Increasing platelet concentration in platelet-rich plasma inhibits anterior cruciate ligament cell function in three-dimensional culture.

PubMed

Yoshida, Ryu; Cheng, Mingyu; Murray, Martha M

2014-02-01

Tissue engineering is one new strategy being developed to treat ACL ruptures. One such approach is bio-enhanced ACL repair, where a suture repair is supplemented with a bio-active scaffold containing platelets. However, the optimal concentration of platelets to stimulate ACL healing is not known. We hypothesized that increasing platelet concentrations in the scaffold would enhance critical cell behaviors. Porcine ACL fibroblasts were obtained from explant culture and suspended in platelet poor plasma (PPP), 1× platelet-rich plasma (PRP), 3× PRP, 5× PRP, or phosphate buffered saline (PBS). The cell suspensions were cultured in a 3D collagen scaffold. Cellular metabolism (MTT assay), apoptosis (TUNEL assay), and gene expression for type I and type III collagen were measured. 1× PRP significantly outperformed 5× PRP in all parameters studied: Type I and III collagen gene expression, apoptosis prevention, and cell metabolism stimulation. ACL fibroblasts cultured with 1× PRP had the highest type I and type III collagen gene expression. 1× PRP and PPP groups had the highest cell metabolism and lowest apoptosis rates. Concentration of platelets had significant effects on the behavior of ACL fibroblasts; thus, it is an important parameter that should be specified in clinical or basic science studies. © 2013 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Platelets and Plasma Proteins Are Both Required to Stimulate Collagen Gene Expression by Anterior Cruciate Ligament Cells in Three-Dimensional Culture

PubMed Central

Cheng, Mingyu; Wang, Hao; Yoshida, Ryu

2010-01-01

Collagen–platelet (PL)-rich plasma composites have shown in vivo potential to stimulate anterior cruciate ligament (ACL) healing at early time points in large animal models. However, little is known about the cellular mechanisms by which the plasma component of these composites may stimulate healing. We hypothesized that the components of PL-rich plasma (PRP), namely the PLs and PL-poor plasma (PPP), would independently significantly influence ACL cell viability and metabolic activity, including collagen gene expression. To test this hypothesis, ACL cells were cultured in a collagen type I hydrogel with PLs, PPP, or the combination of the two (PRP) for 14 days. The inclusion of PLs, PPP, and PRP all significantly reduced the rate of cell apoptosis and enhanced the metabolic activity of fibroblasts in the collagen hydrogel. PLs promoted fibroblast-mediated collagen scaffold contraction, whereas PPP inhibited this contraction. PPP and PRP both promoted cell elongation and the formation of wavy fibrous structure in the scaffolds. The addition of only PLs or only plasma proteins did not significantly enhance gene expression of collagen types I and III but the combination, as PRP, did. Our findings suggest that the addition of both PLs and plasma proteins to collagen hydrogel may be useful in stimulating ACL healing by enhancing ACL cell viability, metabolic activity, and collagen synthesis. PMID:19958169

Inferring dynamic gene regulatory networks in cardiac differentiation through the integration of multi-dimensional data.

PubMed

Gong, Wuming; Koyano-Nakagawa, Naoko; Li, Tongbin; Garry, Daniel J

2015-03-07

Decoding the temporal control of gene expression patterns is key to the understanding of the complex mechanisms that govern developmental decisions during heart development. High-throughput methods have been employed to systematically study the dynamic and coordinated nature of cardiac differentiation at the global level with multiple dimensions. Therefore, there is a pressing need to develop a systems approach to integrate these data from individual studies and infer the dynamic regulatory networks in an unbiased fashion. We developed a two-step strategy to integrate data from (1) temporal RNA-seq, (2) temporal histone modification ChIP-seq, (3) transcription factor (TF) ChIP-seq and (4) gene perturbation experiments to reconstruct the dynamic network during heart development. First, we trained a logistic regression model to predict the probability (LR score) of any base being bound by 543 TFs with known positional weight matrices. Second, four dimensions of data were combined using a time-varying dynamic Bayesian network model to infer the dynamic networks at four developmental stages in the mouse [mouse embryonic stem cells (ESCs), mesoderm (MES), cardiac progenitors (CP) and cardiomyocytes (CM)]. Our method not only infers the time-varying networks between different stages of heart development, but it also identifies the TF binding sites associated with promoter or enhancers of downstream genes. The LR scores of experimentally verified ESCs and heart enhancers were significantly higher than random regions (p <10(-100)), suggesting that a high LR score is a reliable indicator for functional TF binding sites. Our network inference model identified a region with an elevated LR score approximately -9400 bp upstream of the transcriptional start site of Nkx2-5, which overlapped with a previously reported enhancer region (-9435 to -8922 bp). TFs such as Tead1, Gata4, Msx2, and Tgif1 were predicted to bind to this region and participate in the regulation of Nkx2-5 gene expression. Our model also predicted the key regulatory networks for the ESC-MES, MES-CP and CP-CM transitions. We report a novel method to systematically integrate multi-dimensional -omics data and reconstruct the gene regulatory networks. This method will allow one to rapidly determine the cis-modules that regulate key genes during cardiac differentiation.

The usefulness of three-dimensional cell culture in induction of cancer stem cells from esophageal squamous cell carcinoma cell lines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fujiwara, Daisuke; Kato, Kazunori, E-mail: kzkatou@juntendo.ac.jp; Department of Atopy Research Center, Juntendo University School of Medicine, 2-1-1 Hongo, Bunkyo-ku, Tokyo 113-8421

2013-05-17

Highlights: •Spheroids were created from esophageal carcinoma cells using NanoCulture® Plates. •The proportion of strongly ALDH-positive cells increased in 3-D culture. •Expression of cancer stem cell-related genes was enhanced in 3-D culture. •CA-9 expression was enhanced, suggesting hypoxia had been induced in 3-D culture. •Drug resistance was increased. 3-D culture is useful for inducing cancer stem cells. -- Abstract: In recent years, research on resistance to chemotherapy and radiotherapy in cancer treatment has come under the spotlight, and researchers have also begun investigating the relationship between resistance and cancer stem cells. Cancer stem cells are assumed to be present inmore » esophageal cancer, but experimental methods for identification and culture of these cells have not yet been established. To solve this problem, we created spheroids using a NanoCulture® Plate (NCP) for 3-dimensional (3-D) cell culture, which was designed as a means for experimentally reproducing the 3-D structures found in the body. We investigated the potential for induction of cancer stem cells from esophageal cancer cells. Using flow cytometry we analyzed the expression of surface antigen markers CD44, CD133, CD338 (ABCG2), CD318 (CDCP1), and CD326 (EpCAM), which are known cancer stem cell markers. None of these surface antigen markers showed enhanced expression in 3-D cultured cells. We then analyzed aldehyde dehydrogenase (ALDH) enzymatic activity using the ALDEFLUOR reagent, which can identify immature cells such as stem cells and precursor cells. 3-D-cultured cells were strongly positive for ALDH enzyme activity. We also analyzed the expression of the stem cell-related genes Sox-2, Nanog, Oct3/4, and Lin28 using RT-PCR. Expression of Sox-2, Nanog, and Lin28 was enhanced. Analysis of expression of the hypoxic surface antigen marker carbonic anhydrase-9 (CA-9), which is an indicator of cancer stem cell induction and maintenance, revealed that CA-9 expression was enhanced, suggesting that hypoxia had been induced. Comparison of cancer drug resistance using cisplatin and doxorubicin in 3-D-cultured esophageal cancer cells showed that cancer drug resistance had increased. These results indicate that 3-D culture of esophageal squamous cell carcinoma lines is a useful method for inducing cancer stem cells.« less

Characterization of the Mamestra configurata (Lepidoptera: Noctuidae) larval midgut protease complement and adaptation to feeding on artificial diet, Brassica species, and protease inhibitor.

PubMed

Erlandson, Martin A; Hegedus, Dwayne D; Baldwin, Douglas; Noakes, Amy; Toprak, Umut

2010-10-01

The midgut protease profiles from 5th instar Mamestra configurata larvae fed various diets (standard artificial diet, low protein diet, low protein diet with soybean trypsin inhibitor [SBTI], or Brassica napus) were characterized by one-dimensional enzymography in gelatin gels. The gut protease profile of larvae fed B. napus possessed protease activities of molecular masses of approximately 33 and 55 kDa, which were not present in the guts of larvae fed artificial diet. Similarly, larvae fed artificial diet had protease activities of molecular masses of approximately 21, 30, and 100 kDa that were absent in larvae fed B. napus. Protease profiles changed within 12 to 24 h after switching larvae from artificial diet to plant diet and vice versa. The gut protease profiles from larvae fed various other brassicaceous species and lines having different secondary metabolite profiles did not differ despite significant differences in larval growth rates on the different host plants. Genes encoding putative digestive proteolytic enzymes, including four carboxypeptidases, five aminopeptidases, and 48 serine proteases, were identified in cDNA libraries from 4th instar M. configurata midgut tissue. Many of the protease-encoding genes were expressed at similar levels on all diets; however, three chymoptrypsin-like genes (McSP23, McSP27, and McSP37) were expressed at much higher levels on standard artificial diet and diet containing SBTI as was the trypsin-like gene McSP34. The expression of the trypsin-like gene McSP50 was highest on B. napus. The adaptation of M. configurata digestive biochemistry to different diets is discussed in the context of the flexibility of polyphagous insects to changing diet sources.

Integrated In Silico-In Vitro Identification and Characterization of the SH3-Mediated Interaction between Human PTTG and its Cognate Partners in Medulloblastoma.

PubMed

Liu, Jiangang; Wang, Dapeng; Li, Yanyan; Yao, Hui; Zhang, Nan; Zhang, Xuewen; Zhong, Fangping; Huang, Yulun

2018-06-01

The human pituitary tumor-transforming gene is an oncogenic protein which serves as a central hub in the cellular signaling network of medulloblastoma. The protein contains two vicinal PxxP motifs at its C terminus that are potential binding sites of peptide-recognition SH3 domains. Here, a synthetic protocol that integrated in silico analysis and in vitro assay was described to identify the SH3-binding partners of pituitary tumor-transforming gene in the gene expression profile of medulloblastoma. In the procedure, a variety of structurally diverse, non-redundant SH3 domains with high gene expression in medulloblastoma were compiled, and their three-dimensional structures were either manually retrieved from the protein data bank database or computationally modeled through bioinformatics technique. The binding capability of these domains towards the two PxxP-containing peptides m1p: 161 LGPPSPVK 168 and m2p: 168 KMPSPPWE 175 of pituitary tumor-transforming gene were ranked by structure-based scoring and fluorescence-based assay. Consequently, a number of SH3 domains, including MAP3K and PI3K, were found to have moderate or high affinity for m1p and/or m2p. Interestingly, the two overlapping peptides exhibits a distinct binding profile to these identified domain partners, suggesting that the binding selectivity of m1p and m2p is optimized across the medulloblastoma expression spectrum by competing for domain candidates. In addition, two redesigned versions of m1p peptide ware obtained via a structure-based rational mutation approach, which exhibited an increased affinity for the domain as compared to native peptide.

Predicting degree of benefit from adjuvant trastuzumab in NSABP trial B-31.

PubMed

Pogue-Geile, Katherine L; Kim, Chungyeul; Jeong, Jong-Hyeon; Tanaka, Noriko; Bandos, Hanna; Gavin, Patrick G; Fumagalli, Debora; Goldstein, Lynn C; Sneige, Nour; Burandt, Eike; Taniyama, Yusuke; Bohn, Olga L; Lee, Ahwon; Kim, Seung-Il; Reilly, Megan L; Remillard, Matthew Y; Blackmon, Nicole L; Kim, Seong-Rim; Horne, Zachary D; Rastogi, Priya; Fehrenbacher, Louis; Romond, Edward H; Swain, Sandra M; Mamounas, Eleftherios P; Wickerham, D Lawrence; Geyer, Charles E; Costantino, Joseph P; Wolmark, Norman; Paik, Soonmyung

2013-12-04

National Surgical Adjuvant Breast and Bowel Project (NSABP) trial B-31 suggested the efficacy of adjuvant trastuzumab, even in HER2-negative breast cancer. This finding prompted us to develop a predictive model for degree of benefit from trastuzumab using archived tumor blocks from B-31. Case subjects with tumor blocks were randomly divided into discovery (n = 588) and confirmation cohorts (n = 991). A predictive model was built from the discovery cohort through gene expression profiling of 462 genes with nCounter assay. A predefined cut point for the predictive model was tested in the confirmation cohort. Gene-by-treatment interaction was tested with Cox models, and correlations between variables were assessed with Spearman correlation. Principal component analysis was performed on the final set of selected genes. All statistical tests were two-sided. Eight predictive genes associated with HER2 (ERBB2, c17orf37, GRB7) or ER (ESR1, NAT1, GATA3, CA12, IGF1R) were selected for model building. Three-dimensional subset treatment effect pattern plot using two principal components of these genes was used to identify a subset with no benefit from trastuzumab, characterized by intermediate-level ERBB2 and high-level ESR1 mRNA expression. In the confirmation set, the predefined cut points for this model classified patients into three subsets with differential benefit from trastuzumab with hazard ratios of 1.58 (95% confidence interval [CI] = 0.67 to 3.69; P = .29; n = 100), 0.60 (95% CI = 0.41 to 0.89; P = .01; n = 449), and 0.28 (95% CI = 0.20 to 0.41; P < .001; n = 442; P(interaction) between the model and trastuzumab < .001). We developed a gene expression-based predictive model for degree of benefit from trastuzumab and demonstrated that HER2-negative tumors belong to the moderate benefit group, thus providing justification for testing trastuzumab in HER2-negative patients (NSABP B-47).

Cross-species microarray hybridization to identify developmentally regulated genes in the filamentous fungus Sordaria macrospora.

PubMed

Nowrousian, Minou; Ringelberg, Carol; Dunlap, Jay C; Loros, Jennifer J; Kück, Ulrich

2005-04-01

The filamentous fungus Sordaria macrospora forms complex three-dimensional fruiting bodies that protect the developing ascospores and ensure their proper discharge. Several regulatory genes essential for fruiting body development were previously isolated by complementation of the sterile mutants pro1, pro11 and pro22. To establish the genetic relationships between these genes and to identify downstream targets, we have conducted cross-species microarray hybridizations using cDNA arrays derived from the closely related fungus Neurospora crassa and RNA probes prepared from wild-type S. macrospora and the three developmental mutants. Of the 1,420 genes which gave a signal with the probes from all the strains used, 172 (12%) were regulated differently in at least one of the three mutants compared to the wild type, and 17 (1.2%) were regulated differently in all three mutant strains. Microarray data were verified by Northern analysis or quantitative real time PCR. Among the genes that are up- or down-regulated in the mutant strains are genes encoding the pheromone precursors, enzymes involved in melanin biosynthesis and a lectin-like protein. Analysis of gene expression in double mutants revealed a complex network of interaction between the pro gene products.

Analysis tools for the interplay between genome layout and regulation.

PubMed

Bouyioukos, Costas; Elati, Mohamed; Képès, François

2016-06-06

Genome layout and gene regulation appear to be interdependent. Understanding this interdependence is key to exploring the dynamic nature of chromosome conformation and to engineering functional genomes. Evidence for non-random genome layout, defined as the relative positioning of either co-functional or co-regulated genes, stems from two main approaches. Firstly, the analysis of contiguous genome segments across species, has highlighted the conservation of gene arrangement (synteny) along chromosomal regions. Secondly, the study of long-range interactions along a chromosome has emphasised regularities in the positioning of microbial genes that are co-regulated, co-expressed or evolutionarily correlated. While one-dimensional pattern analysis is a mature field, it is often powerless on biological datasets which tend to be incomplete, and partly incorrect. Moreover, there is a lack of comprehensive, user-friendly tools to systematically analyse, visualise, integrate and exploit regularities along genomes. Here we present the Genome REgulatory and Architecture Tools SCAN (GREAT:SCAN) software for the systematic study of the interplay between genome layout and gene expression regulation. SCAN is a collection of related and interconnected applications currently able to perform systematic analyses of genome regularities as well as to improve transcription factor binding sites (TFBS) and gene regulatory network predictions based on gene positional information. We demonstrate the capabilities of these tools by studying on one hand the regular patterns of genome layout in the major regulons of the bacterium Escherichia coli. On the other hand, we demonstrate the capabilities to improve TFBS prediction in microbes. Finally, we highlight, by visualisation of multivariate techniques, the interplay between position and sequence information for effective transcription regulation.

T4 AsiA blocks DNA recognition by remodeling σ70 region 4

PubMed Central

Lambert, Lester J; Wei, Yufeng; Schirf, Virgil; Demeler, Borries; Werner, Milton H

2004-01-01

Bacteriophage T4 AsiA is a versatile transcription factor capable of inhibiting host gene expression as an ‘anti-σ′ factor while simultaneously promoting gene-specific expression of T4 middle genes in conjunction with T4 MotA. To accomplish this task, AsiA engages conserved region 4 of Eschericia coli σ70, blocking recognition of most host promoters by sequestering the DNA-binding surface at the AsiA/σ70 interface. The three-dimensional structure of an AsiA/region 4 complex reveals that the C-terminal α helix of region 4 is unstructured, while four other helices adopt a completely different conformation relative to the canonical structure of unbound region 4. That AsiA induces, rather than merely stabilizes, this rearrangement can be realized by comparison to the homologous structures of region 4 solved in a variety of contexts, including the structure of Thermotoga maritima σA region 4 described herein. AsiA simultaneously occupies the surface of region 4 that ordinarily contacts core RNA polymerase (RNAP), suggesting that an AsiA-bound σ70 may also undergo conformational changes in the context of the RNAP holoenzyme. PMID:15257291

[Regulation of in vitro and in vivo differentiation of mouse embryonic stem cells, embryonic germ cells, and teratocarcinoma cells by TGFb family signaling factors].

PubMed

Gordeeva, O F; Nikonova, T M; Lifantseva, N V

2009-01-01

The activity of specific signaling and transcription factors determines the cell fate in normal development and in tumor transformation. The transcriptional profiles of gene-components of different branches of TGFbeta family signaling pathways were studied in experimental models of initial stages of three-dimensional in vitro differentiation of embryonic stem cells, embryonic germ cells and teratocarcinoma cells and in teratomas and teratocarcinomas developed after their transplantation into immunodeficient Nude mice. Gene profile analysis of studied cell systems have revealed that expression patterns of ActivinA, Nodal, Lefty1, Lefty2, TGF TGFbeta1, BMP4, and GDF were identical in pluripotent stem cells whereas the mRNAs of all examined genes with the exception of Inhibin betaA/ActivinA were detected in the teratocarcinoma cells. These results indicate that differential activity of signaling pathways of the TGFbeta family factors regulates pluripotent state maintenance and pluripotent stem cell differentiation into the progenitors of three germ layers and extraembryonic structures and that normal expression pattern of TGFbeta family factors is rearranged in embryonic teratocarcinoma cells during tumor growth in vitro and in vivo.

An Improved Method for TAL Effectors DNA-Binding Sites Prediction Reveals Functional Convergence in TAL Repertoires of Xanthomonas oryzae Strains

PubMed Central

Pérez-Quintero, Alvaro L.; Rodriguez-R, Luis M.; Dereeper, Alexis; López, Camilo; Koebnik, Ralf; Szurek, Boris; Cunnac, Sebastien

2013-01-01

Transcription Activators-Like Effectors (TALEs) belong to a family of virulence proteins from the Xanthomonas genus of bacterial plant pathogens that are translocated into the plant cell. In the nucleus, TALEs act as transcription factors inducing the expression of susceptibility genes. A code for TALE-DNA binding specificity and high-resolution three-dimensional structures of TALE-DNA complexes were recently reported. Accurate prediction of TAL Effector Binding Elements (EBEs) is essential to elucidate the biological functions of the many sequenced TALEs as well as for robust design of artificial TALE DNA-binding domains in biotechnological applications. In this work a program with improved EBE prediction performances was developed using an updated specificity matrix and a position weight correction function to account for the matching pattern observed in a validation set of TALE-DNA interactions. To gain a systems perspective on the large TALE repertoires from X. oryzae strains, this program was used to predict rice gene targets for 99 sequenced family members. Integrating predictions and available expression data in a TALE-gene network revealed multiple candidate transcriptional targets for many TALEs as well as several possible instances of functional convergence among TALEs. PMID:23869221

The Two-Component System PhoPR of Clostridium acetobutylicum Is Involved in Phosphate-Dependent Gene Regulation ▿

PubMed Central

Fiedler, Tomas; Mix, Maren; Meyer, Uta; Mikkat, Stefan; Glocker, Michael O.; Bahl, Hubert; Fischer, Ralf-Jörg

2008-01-01

The phoPR gene locus of Clostridium acetobutylicum ATCC 824 comprises two genes, phoP and phoR. Deduced proteins are predicted to represent a response regulator and sensor kinase of a phosphate-dependent two-component regulatory system. We analyzed the expression patterns of phoPR in Pi-limited chemostat cultures and in response to Pi pulses. A basic transcription level under high-phosphate conditions was shown, and a significant increase in mRNA transcript levels was found when external Pi concentrations dropped below 0.3 mM. In two-dimensional gel electrophoresis experiments, a 2.5-fold increase in PhoP was observed under Pi-limiting growth conditions compared to growth with an excess of Pi. At least three different transcription start points for phoP were determined by primer extension analyses. Proteins PhoP and an N-terminally truncated *PhoR were individually expressed heterologously in Escherichia coli and purified. Autophosphorylation of *PhoR and phosphorylation of PhoP were shown in vitro. Electromobility shift assays proved that there was a specific binding of PhoP to the promoter region of the phosphate-regulated pst operon of C. acetobutylicum. PMID:18689481

Genome Expression Pathway Analysis Tool – Analysis and visualization of microarray gene expression data under genomic, proteomic and metabolic context

PubMed Central

Weniger, Markus; Engelmann, Julia C; Schultz, Jörg

2007-01-01

Background Regulation of gene expression is relevant to many areas of biology and medicine, in the study of treatments, diseases, and developmental stages. Microarrays can be used to measure the expression level of thousands of mRNAs at the same time, allowing insight into or comparison of different cellular conditions. The data derived out of microarray experiments is highly dimensional and often noisy, and interpretation of the results can get intricate. Although programs for the statistical analysis of microarray data exist, most of them lack an integration of analysis results and biological interpretation. Results We have developed GEPAT, Genome Expression Pathway Analysis Tool, offering an analysis of gene expression data under genomic, proteomic and metabolic context. We provide an integration of statistical methods for data import and data analysis together with a biological interpretation for subsets of probes or single probes on the chip. GEPAT imports various types of oligonucleotide and cDNA array data formats. Different normalization methods can be applied to the data, afterwards data annotation is performed. After import, GEPAT offers various statistical data analysis methods, as hierarchical, k-means and PCA clustering, a linear model based t-test or chromosomal profile comparison. The results of the analysis can be interpreted by enrichment of biological terms, pathway analysis or interaction networks. Different biological databases are included, to give various information for each probe on the chip. GEPAT offers no linear work flow, but allows the usage of any subset of probes and samples as a start for a new data analysis. GEPAT relies on established data analysis packages, offers a modular approach for an easy extension, and can be run on a computer grid to allow a large number of users. It is freely available under the LGPL open source license for academic and commercial users at . Conclusion GEPAT is a modular, scalable and professional-grade software integrating analysis and interpretation of microarray gene expression data. An installation available for academic users can be found at . PMID:17543125

A Heterogeneous Network Based Method for Identifying GBM-Related Genes by Integrating Multi-Dimensional Data.

PubMed

Chen Peng; Ao Li

2017-01-01

The emergence of multi-dimensional data offers opportunities for more comprehensive analysis of the molecular characteristics of human diseases and therefore improving diagnosis, treatment, and prevention. In this study, we proposed a heterogeneous network based method by integrating multi-dimensional data (HNMD) to identify GBM-related genes. The novelty of the method lies in that the multi-dimensional data of GBM from TCGA dataset that provide comprehensive information of genes, are combined with protein-protein interactions to construct a weighted heterogeneous network, which reflects both the general and disease-specific relationships between genes. In addition, a propagation algorithm with resistance is introduced to precisely score and rank GBM-related genes. The results of comprehensive performance evaluation show that the proposed method significantly outperforms the network based methods with single-dimensional data and other existing approaches. Subsequent analysis of the top ranked genes suggests they may be functionally implicated in GBM, which further corroborates the superiority of the proposed method. The source code and the results of HNMD can be downloaded from the following URL: http://bioinformatics.ustc.edu.cn/hnmd/ .

Difference in suitable mechanical properties of three-dimensional, synthetic scaffolds for self-renewing mouse embryonic stem cells of different genetic backgrounds.

PubMed

Lee, Myungook; Ahn, Jong Il; Ahn, Ji Yeon; Yang, Woo Sub; Hubbell, Jeffrey A; Lim, Jeong Mook; Lee, Seung Tae

2017-11-01

We evaluated whether the genetic background of embryonic stem cells (ESCs) affects the properties suitable for three-dimensional (3D) synthetic scaffolds for cell self-renewal. Inbred R1 and hybrid B6D2F1 mouse ESC lines were cultured for 7 days in hydrogel scaffolds with different properties derived from conjugating 7.5, 10, 12.5, or 15% (wt/vol) vinylsulfone-functionalized three-, four-, or eight-arm polyethylene glycol (PEG) with dicysteine-containing crosslinkers with an intervening matrix metalloproteinase-specific cleavage sites. Cell proliferation and expression of self-renewal-related genes and proteins by ESCs cultured in feeder-free or containing 2D culture plate or 3D hydrogel were monitored. As a preliminary experiment, the E14 ESC-customized synthetic 3D microenvironment did not maintain self-renewal of either the R1 or B6D2F1 ESCs. The best R1 cell proliferation (10.04 vs. 0.16-4.39; p < 0.0001) was observed in the four-arm 7.5% PEG-based hydrogels than those with other properties, whereas the F1 ESCs showed better proliferation when they were embedded in the three-arm 10% hydrogels. Self-renewal-related gene and protein expression by ESCs after feeder-free 3D culture was generally maintained compared with the feeder-containing 2D culture, but expression patterns and quantities differed. However, the feeder-free 3D culture yielded better expression than the feeder-free 2D culture. In conclusion, genetic background determined the suitability of hydrogel scaffolds for self-renewal of ESCs, which requires customization for the mechanical properties of each cell line. © 2016 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 105B: 2261-2268, 2017. © 2016 Wiley Periodicals, Inc.

3D-printed gelatin scaffolds of differing pore geometry modulate hepatocyte function and gene expression.

PubMed

Lewis, Phillip L; Green, Richard M; Shah, Ramille N

2018-03-15

Three dimensional (3D) printing is highly amenable to the fabrication of tissue-engineered organs of a repetitive microstructure such as the liver. The creation of uniform and geometrically repetitive tissue scaffolds can also allow for the control over cellular aggregation and nutrient diffusion. However, the effect of differing geometries, while controlling for pore size, has yet to be investigated in the context of hepatocyte function. In this study, we show the ability to precisely control pore geometry of 3D-printed gelatin scaffolds. An undifferentiated hepatocyte cell line (HUH7) demonstrated high viability and proliferation when seeded on 3D-printed scaffolds of two different geometries. However, hepatocyte specific functions (albumin secretion, CYP activity, and bile transport) increases in more interconnected 3D-printed gelatin cultures compared to a less interconnected geometry and to 2D controls. Additionally, we also illustrate the disparity between gene expression and protein function in simple 2D culture modes, and that recreation of a physiologically mimetic 3D environment is necessary to induce both expression and function of cultured hepatocytes. Three dimensional (3D) printing provides tissue engineers the ability spatially pattern cells and materials in precise geometries, however the biological effects of scaffold geometry on soft tissues such as the liver have not been rigorously investigated. In this manuscript, we describe a method to 3D print gelatin into well-defined repetitive geometries that show clear differences in biological effects on seeded hepatocytes. We show that a relatively simple and widely used biomaterial, such as gelatin, can significantly modulate biological processes when fabricated into specific 3D geometries. Furthermore, this study expands upon past research into hepatocyte aggregation by demonstrating how it can be manipulated to enhance protein function, and how function and expression may not precisely correlate in 2D models. Copyright © 2018 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Universal monitoring of minimal residual disease in acute myeloid leukemia.

PubMed

Coustan-Smith, Elaine; Song, Guangchun; Shurtleff, Sheila; Yeoh, Allen Eng-Juh; Chng, Wee Joo; Chen, Siew Peng; Rubnitz, Jeffrey E; Pui, Ching-Hon; Downing, James R; Campana, Dario

2018-05-03

Optimal management of acute myeloid leukemia (AML) requires monitoring of treatment response, but minimal residual disease (MRD) may escape detection. We sought to identify distinctive features of AML cells for universal MRD monitoring. We compared genome-wide gene expression of AML cells from 157 patients with that of normal myeloblasts. Markers encoded by aberrantly expressed genes, including some previously associated with leukemia stem cells, were studied by flow cytometry in 240 patients with AML and in nonleukemic myeloblasts from 63 bone marrow samples. Twenty-two (CD9, CD18, CD25, CD32, CD44, CD47, CD52, CD54, CD59, CD64, CD68, CD86, CD93, CD96, CD97, CD99, CD123, CD200, CD300a/c, CD366, CD371, and CX3CR1) markers were aberrantly expressed in AML. Leukemia-associated profiles defined by these markers extended to immature CD34+CD38- AML cells; expression remained stable during treatment. The markers yielded MRD measurements matching those of standard methods in 208 samples from 52 patients undergoing chemotherapy and revealed otherwise undetectable MRD. They allowed MRD monitoring in 129 consecutive patients, yielding prognostically significant results. Using a machine-learning algorithm to reduce high-dimensional data sets to 2-dimensional data, the markers allowed a clear visualization of MRD and could detect 1 leukemic cell among more than 100,000 normal cells. The markers uncovered in this study allow universal and sensitive monitoring of MRD in AML. In combination with contemporary analytical tools, the markers improve the discrimination between leukemic and normal cells, thus facilitating data interpretation and, hence, the reliability of MRD results. National Cancer Institute (CA60419 and CA21765); American Lebanese Syrian Associated Charities; National Medical Research Council of Singapore (1299/2011); Viva Foundation for Children with Cancer, Children's Cancer Foundation, Tote Board & Turf Club, and Lee Foundation of Singapore.

A Novel Notch-YAP Circuit Drives Stemness and Tumorigenesis in Embryonal Rhabdomyosarcoma.

PubMed

Slemmons, Katherine K; Crose, Lisa E S; Riedel, Stefan; Sushnitha, Manuela; Belyea, Brian; Linardic, Corinne M

2017-12-01

Rhabdomyosarcoma (RMS), a cancer characterized by skeletal muscle features, is the most common soft-tissue sarcoma of childhood. While low- and intermediate-risk groups have seen improved outcomes, high-risk patients still face a 5-year survival rate of <30%, a statistic that has not changed in over 40 years. Understanding the biologic underpinnings of RMS is critical. The developmental pathways of Notch and YAP have been identified as potent but independent oncogenic signals that support the embryonal variant of RMS (eRMS). Here, the cross-talk between these pathways and the impact on eRMS tumorigenesis is reported. Using human eRMS cells grown as three-dimensional (3D) rhabdospheres, which enriches in stem cells, it was found that Notch signaling transcriptionally upregulates YAP1 gene expression and YAP activity. Reciprocally, YAP transcriptionally upregulates the Notch ligand genes JAG1 and DLL1 and the core Notch transcription factor RBPJ This bidirectional circuit boosts expression of key stem cell genes, including SOX2 , which is functionally required for eRMS spheres. Silencing this circuit for therapeutic purposes may be challenging, because the inhibition of one node (e.g., pharmacologic Notch blockade) can be rescued by upregulation of another (constitutive YAP expression). Instead, dual inhibition of Notch and YAP is necessary. Finally, supporting the existence of this circuit beyond a model system, nuclear Notch and YAP protein expression are correlated in human eRMS tumors, and YAP suppression in vivo decreases Notch signaling and SOX2 expression. Implications: This study identifies a novel oncogenic signaling circuit driving eRMS stemness and tumorigenesis, and provides evidence and rationale for combination therapies co-targeting Notch and YAP. Mol Cancer Res; 15(12); 1777-91. ©2017 AACR . ©2017 American Association for Cancer Research.

Differential Response of Bovine Mature Nucleus Pulposus and Notochordal Cells to Hydrostatic Pressure and Glucose Restriction.

PubMed

Saggese, Taryn; Thambyah, Ashvin; Wade, Kelly; McGlashan, Susan Read

2018-05-01

Objective The nucleus pulposus of the human intervertebral disc contains 2 cell types: notochordal (NC) and mature nucleus pulposus (MNP) cells. NC cell loss is associated with disc degeneration and this process may be initiated by mechanical stress and/or nutrient deprivation. This study aimed to investigate the functional responses of NC and MNP cells to hydrostatic pressures and glucose restriction. Design Bovine MNP and NC cells were cultured in 3-dimensional alginate beads under low (0.4-0.8 MPa) and high (1.6-2.4 MPa) dynamic pressure for 24 hours. Cells were cultured in either physiological (5.5 mM) glucose media or glucose-restriction (0.55 mM) media. Finally, the combined effect of glucose restriction and high pressure was examined. Results Cell viability and notochordal phenotypic markers were not significantly altered in response to pressure or glucose restriction. MNP cells responded to low pressure with an increase in glycosaminoglycan (GAG) production while high pressure significantly decreased ACAN gene expression compared with atmospheric controls. NC cells showed no response in matrix gene expression or GAG production with either loading regime. Glucose restriction decreased NC cell TIMP-1 expression but had no effect on MNP cells. The combination of glucose restriction and high pressure only affected MNP cell gene expression, with decreased ACAN, Col2α1, and ADAMTS-5 expression. Conclusion This study shows that NC cells are more resistant to acute mechanical stresses than MNP cells and provides a strong rationale for future studies to further our understanding the role of NC cells within the disc, and the effects of long-term exposure to physical stresses.

The adipokine adiponectin has potent anti-fibrotic effects mediated via adenosine monophosphate-activated protein kinase: novel target for fibrosis therapy

PubMed Central

2012-01-01

Introduction Fibrosis in scleroderma is associated with collagen deposition and myofibroblast accumulation. Peroxisome proliferator activated receptor gamma (PPAR-γ), a master regulator of adipogenesis, inhibits profibrotic responses induced by transforming growth factor-ß (TGF-β), and its expression is impaired in scleroderma. The roles of adiponectin, a PPAR-γ regulated pleiotropic adipokine, in regulating the response of fibroblasts and in mediating the effects of PPAR-γ are unknown. Methods Regulation of fibrotic gene expression and TGF-ß signaling by adiponectin and adenosine monophosphate protein-activated (AMP) kinase agonists were examined in normal fibroblasts in monolayer cultures and in three-dimensional skin equivalents. AdipoR1/2 expression on skin fibroblasts was determined by real-time quantitative PCR. Results Adiponectin, an adipokine directly regulated by PPAR-γ, acts as a potent anti-fibrotic signal in normal and scleroderma fibroblasts that abrogates the stimulatory effects of diverse fibrotic stimuli and reduces elevated collagen gene expression in scleroderma fibroblasts. Adiponectin responses are mediated via AMP kinase, a fuel-sensing cellular enzyme that is necessary and sufficient for down-regulation of fibrotic genes by blocking canonical Smad signaling. Moreover, we demonstrate that endogenous adiponectin accounts, at least in part, for the anti-fibrotic effects exerted by ligands of PPAR-γ. Conclusions These findings reveal a novel link between cellular energy metabolism and extracellular matrix homeostasis converging on AMP kinase. Since the levels of adiponectin as well as its receptor are impaired in scleroderma patients with progressive fibrosis, the present results suggest a potential role for defective adiponectin expression or function in progressive fibrogenesis in scleroderma and other chronic fibrosing conditions. Restoring the adiponectin signaling axis in fibroblasts might, therefore, represent a novel pharmacological approach to controlling fibrosis. PMID:23092446

Ethylene Regulates Monomeric GTP-Binding Protein Gene Expression and Activity in Arabidopsis1

PubMed Central

Moshkov, Igor E.; Mur, Luis A.J.; Novikova, Galina V.; Smith, Aileen R.; Hall, Michael A.

2003-01-01

Ethylene rapidly and transiently up-regulates the activity of several monomeric GTP-binding proteins (monomeric G proteins) in leaves of Arabidopsis as determined by two-dimensional gel electrophoresis and autoradiographic analyses. The activation is suppressed by the receptor-directed inhibitor 1-methylcyclopropene. In the etr1-1 mutant, constitutive activity of all the monomeric G proteins activated by ethylene is down-regulated relative to wild type, and ethylene treatment has no effect on the levels of activity. Conversely, in the ctr1-1 mutant, several of the monomeric G proteins activated by ethylene are constitutively up-regulated. However, the activation profile of ctr1-1 does not exactly mimic that of ethylene-treated wild type. Biochemical and molecular evidence suggested that some of these monomeric G proteins are of the Rab class. Expression of the genes for a number of monomeric G proteins in response to ethylene was investigated by reverse transcriptase-PCR. Rab8 and Ara3 expression was increased within 10 min of ethylene treatment, although levels fell back significantly by 40 min. In the etr1-1 mutant, expression of Rab8 was lower than wild type and unaffected by ethylene; in ctr1-1, expression of Rab8 was much higher than wild type and comparable with that seen in ethylene treatments. Expression in ctr1-1 was also unaffected by ethylene. Thus, the data indicate a role for monomeric G proteins in ethylene signal transduction. PMID:12692329

Protein Expression Profile using Two-Dimensional Gel Analysis in Squamous Cervical Cancer Patients

PubMed Central

Bae, Su-Mi; Min, Hyun-Jin; Ding, Guo Hua; Kwak, Sun-Young; Cho, Young-Lae; Nam, Kye-Hyun; Park, Choong Hak; Kim, Yong-Wan; Kim, Chong-Kook; Han, Byoung-Don; Lee, Young-Joo; Kim, Do Kang

2006-01-01

Purpose Screening in cervical cancer is now progressing to discover candidate genes and proteins that may serve as biological markers and that play a role in tumor progression. We examined the protein expression patterns of the squamous cell carcinoma (SCC) tissues from Korean women with using two- dimensional polyacrylamide gel electrophoresis (2-DE) and matrix assisted laser desorption/ionization-time of flight (MALDI- TOF) mass spectrometer. Materials and Methods Normal cervix and SCC tissues were solubilized and 2-DE was performed using pH 3~10 linear IPG strips of 17 cm length. The protein expression was evaluated using PDQuest 2-D software™. The differentially expressed protein spots were identified with a MALDI-TOF mass spectrometer, and the peptide mass spectra identifications were performed using the Mascot program and by searching the Swiss-prot or NCBInr databases. Results A total of 35 proteins were detected in SCC. 17 proteins were up-regulated and 18 proteins weredown-regulated. Among the proteins that were identified, 12 proteins (pigment epithelium derived factor, annexin A2 and A5, keratin 19 and 20, heat shock protein 27, smooth muscle protein 22 alpha, α-enolase, squamous cell carcinoma antigen 1 and 2, glutathione S-transferase and apolipoprotein a1) were protein previously known to be involved in tumor, and 21 proteins were newly identified in this study. Conclusion 2-DE offers the total protein expression profiles of SCC tissues; further characterization of these differentially expressed proteins will give a chance to identify the badly needed tumor-specific diagnostic markers for SCC. PMID:19771267

In silico design, construction and cloning of Trastuzumab humanized monoclonal antibody: A possible biosimilar for Herceptin

PubMed Central

Akbarzadeh-Sharbaf, Soudabeh; Yakhchali, Bagher; Minuchehr, Zarrin; Shokrgozar, Mohammad Ali; Zeinali, Sirous

2012-01-01

Background: There is a novel hypothesis in that antibodies may have specificity for two distinct antigens that have been named “dual specificity”. This hypothesis was evaluated for some defined therapeutic monoclonal antibodies (mAbs) such as Trastuzumab, Pertuzumab, Bevacizumab, and Cetuximab. In silico design and construction of expression vectors for trastuzumab monoclonal antibody also in this work were performed. Materials and Methods: First, in bioinformatics studies the 3D structures of concerned mAbs were obtained from the Protein Data Bank (PDB). Three-dimensional structural alignments were performed with SIM and MUSTANG softwares. AutoDock4.2 software also was used for the docking analysis. Second, the suitable genes for trastuzumab heavy and light chains were designed, synthesized, and cloned in the prokaryotic vector. These fragments individually were PCR amplified and cloned into pcDNA™ 3.3-TOPO® and pOptiVEC™ TOPO® shuttle vectors, using standard methods. Results: First, many bioinformatics tools and softwares were applied but we did not meet any new dual specificity in the selected antibodies. In the following step, the suitable expression cascade for the heavy and light chains of Trastuzumab therapeutic mAb were designed and constructed. Gene cloning was successfully performed and created constructs were confirmed using gene mapping and sequencing. Conclusions: This study was based on a recently developed technology for mAb expression in mammalian cells. The obtained constructs could be successfully used for biosimilar recombinant mAb production in CHO DG44 dihydrofolate reductase (DHFR) gene deficient cell line in the suspension culture medium. PMID:23210080

Three-dimensional culture of buffalo granulosa cells in hanging drop mimics the preovulatory follicle stage.

PubMed

Yadav, Monica; Agrawal, Himanshu; Pandey, Mamta; Singh, Dheer; Onteru, Suneel K

2018-03-01

Granulosa cell (GC) culture models mimicking the intrafollicular environment are limited. Such models have a great potential in reproductive toxicity studies. The buffalo, a monovulatory species like humans, could be a better model than polyovulatory rodents. Therefore, we targeted the development and characterization of three-dimensional (3D) culture systems for buffalo GCs. The GCs from small ovarian follicles (SF) maintained the CYP19 gene expression for 144 hr in a 2D culture system. Hence, GCs from SF were cultured directly in 3D using hanging drop and Poly-([2-hydroxyethyl methacrylate]) (polyHEMA) methods in the DMEM media containing 1 ng/ml FSH and 10 ng/ml IGF-1 for 144 hr. The expression profile of nine GC-specific transcripts; CYP19, TNFAIP6, AMH, PTI, NR4A1, FSHR, RUNX, LHR, and COX2/PTGS2; revealed that 3D-spheroids developed in hanging drop method maintained the GC phenotype of preovulatory follicles. Therefore, hanging drop method is a best method for culturing GCs to mimic the intrafollicular environment. © 2017 Wiley Periodicals, Inc.

Linear Regression Links Transcriptomic Data and Cellular Raman Spectra.

PubMed

Kobayashi-Kirschvink, Koseki J; Nakaoka, Hidenori; Oda, Arisa; Kamei, Ken-Ichiro F; Nosho, Kazuki; Fukushima, Hiroko; Kanesaki, Yu; Yajima, Shunsuke; Masaki, Haruhiko; Ohta, Kunihiro; Wakamoto, Yuichi

2018-06-08

Raman microscopy is an imaging technique that has been applied to assess molecular compositions of living cells to characterize cell types and states. However, owing to the diverse molecular species in cells and challenges of assigning peaks to specific molecules, it has not been clear how to interpret cellular Raman spectra. Here, we provide firm evidence that cellular Raman spectra and transcriptomic profiles of Schizosaccharomyces pombe and Escherichia coli can be computationally connected and thus interpreted. We find that the dimensions of high-dimensional Raman spectra and transcriptomes measured by RNA sequencing can be reduced and connected linearly through a shared low-dimensional subspace. Accordingly, we were able to predict global gene expression profiles by applying the calculated transformation matrix to Raman spectra, and vice versa. Highly expressed non-coding RNAs contributed to the Raman-transcriptome linear correspondence more significantly than mRNAs in S. pombe. This demonstration of correspondence between cellular Raman spectra and transcriptomes is a promising step toward establishing spectroscopic live-cell omics studies. Copyright © 2018 Elsevier Inc. All rights reserved.

Candidate gene analyses of 3-dimensional dentoalveolar phenotypes in subjects with malocclusion

PubMed Central

Weaver, Cole A.; Miller, Steven F.; da Fontoura, Clarissa S. G.; Wehby, George L.; Amendt, Brad A.; Holton, Nathan E.; Allareddy, Veeratrishul; Southard, Thomas E.; Moreno Uribe, Lina M.

2017-01-01

Introduction Genetic studies of malocclusion etiology have identified 4 deleterious mutations in genes, DUSP6, ARHGAP21, FGF23, and ADAMTS1 in familial Class III cases. Although these variants may have large impacts on Class III phenotypic expression, their low frequency (<1%) makes them unlikely to explain most malocclusions. Thus, much of the genetic variation underlying the dentofacial phenotypic variation associated with malocclusion remains unknown. In this study, we evaluated associations between common genetic variations in craniofacial candidate genes and 3-dimensional dentoalveolar phenotypes in patients with malocclusion. Methods Pretreatment dental casts or cone-beam computed tomographic images from 300 healthy subjects were digitized with 48 landmarks. The 3-dimensional coordinate data were submitted to a geometric morphometric approach along with principal component analysis to generate continuous phenotypes including symmetric and asymmetric components of dentoalveolar shape variation, fluctuating asymmetry, and size. The subjects were genotyped for 222 single-nucleotide polymorphisms in 82 genes/loci, and phenotpye-genotype associations were tested via multivariate linear regression. Results Principal component analysis of symmetric variation identified 4 components that explained 68% of the total variance and depicted anteroposterior, vertical, and transverse dentoalveolar discrepancies. Suggestive associations (P < 0.05) were identified with PITX2, SNAI3, 11q22.2-q22.3, 4p16.1, ISL1, and FGF8. Principal component analysis for asymmetric variations identified 4 components that explained 51% of the total variations and captured left-to-right discrepancies resulting in midline deviations, unilateral crossbites, and ectopic eruptions. Suggestive associations were found with TBX1 AJUBA, SNAI3 SATB2, TP63, and 1p22.1. Fluctuating asymmetry was associated with BMP3 and LATS1. Associations for SATB2 and BMP3 with asymmetric variations remained significant after the Bonferroni correction (P <0.00022). Suggestive associations were found for centroid size, a proxy for dentoalveolar size variation with 4p16.1 and SNAI1. Conclusions Specific genetic pathways associated with 3-dimensional dentoalveolar phenotypic variation in malocclusions were identified. PMID:28257739

Molecular cloning, structural analysis, and expression in Escherichia coli of a chitinase gene from Enterobacter agglomerans.

PubMed Central

Chernin, L S; De la Fuente, L; Sobolev, V; Haran, S; Vorgias, C E; Oppenheim, A B; Chet, I

1997-01-01

The gene chiA, which codes for endochitinase, was cloned from a soilborne Enterobacter agglomerans. Its complete sequence was determined, and the deduced amino acid sequence of the enzyme designated Chia_Entag yielded an open reading frame coding for 562 amino acids of a 61-kDa precursor protein with a putative leader peptide at its N terminus. The nucleotide and polypeptide sequences of Chia_Entag showed 86.8 and 87.7% identity with the corresponding gene and enzyme, Chia_Serma, of Serratia marcescens, respectively. Homology modeling of Chia_Entag's three-dimensional structure demonstrated that most amino acid substitutions are at solvent-accessible sites. Escherichia coli JM109 carrying the E. agglomerans chiA gene produced and secreted Chia_Entag. The antifungal activity of the secreted endochitinase was demonstrated in vitro by inhibition of Fusarium oxysporum spore germination. The transformed strain inhibited Rhizoctonia solani growth on plates and the root rot disease caused by this fungus in cotton seedlings under greenhouse conditions. PMID:9055404

Identification of the electron transfer flavoprotein as an upregulated enzyme in the benzoate utilization of Desulfotignum balticum.

PubMed

Habe, Hiroshi; Kobuna, Akinori; Hosoda, Akifumi; Kosaka, Tomoyuki; Endoh, Takayuki; Tamura, Hiroto; Yamane, Hisakazu; Nojiri, Hideaki; Omori, Toshio; Watanabe, Kazuya

2009-07-01

Desulfotignum balticum utilizes benzoate coupled to sulfate reduction. Two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) analysis was conducted to detect proteins that increased more after growth on benzoate than on butyrate. A comparison of proteins on 2D gels showed that at least six proteins were expressed. The N-terminal sequences of three proteins exhibited significant identities with the alpha and beta subunits of electron transfer flavoprotein (ETF) from anaerobic aromatic-degraders. By sequence analysis of the fosmid clone insert (37,590 bp) containing the genes encoding the ETF subunits, we identified three genes, whose deduced amino acid sequences showed 58%, 74%, and 62% identity with those of Gmet_2267 (Fe-S oxidoreductase), Gmet_2266 (ETF beta subunit), and Gmet_2265 (ETF alpha subunit) respectively, which exist within the 300-kb genomic island of aromatic-degradation genes from Geobacter metallireducens GS-15. The genes encoding ETF subunits found in this study were upregulated in benzoate utilization.

Linking structural biology with genome research: Beamlines for the Berlin ``Protein Structure Factory'' initiative

NASA Astrophysics Data System (ADS)

Illing, Gerd; Saenger, Wolfram; Heinemann, Udo

2000-06-01

The Protein Structure Factory will be established to characterize proteins encoded by human genes or cDNAs, which will be selected by criteria of potential structural novelty or medical or biotechnological usefulness. It represents an integrative approach to structure analysis combining bioinformatics techniques, automated gene expression and purification of gene products, generation of a biophysical fingerprint of the proteins and the determination of their three-dimensional structures either by NMR spectroscopy or by X-ray diffraction. The use of synchrotron radiation will be crucial to the Protein Structure Factory: high brilliance and tunable wavelengths are prerequisites for fast data collection, the use of small crystals and multiwavelength anomalous diffraction (MAD) phasing. With the opening of BESSY II, direct access to a third-generation XUV storage ring source with excellent conditions is available nearby. An insertion device with two MAD beamlines and one constant energy station will be set up until 2001.

Finding Groups in Gene Expression Data

PubMed Central

2005-01-01

The vast potential of the genomic insight offered by microarray technologies has led to their widespread use since they were introduced a decade ago. Application areas include gene function discovery, disease diagnosis, and inferring regulatory networks. Microarray experiments enable large-scale, high-throughput investigations of gene activity and have thus provided the data analyst with a distinctive, high-dimensional field of study. Many questions in this field relate to finding subgroups of data profiles which are very similar. A popular type of exploratory tool for finding subgroups is cluster analysis, and many different flavors of algorithms have been used and indeed tailored for microarray data. Cluster analysis, however, implies a partitioning of the entire data set, and this does not always match the objective. Sometimes pattern discovery or bump hunting tools are more appropriate. This paper reviews these various tools for finding interesting subgroups. PMID:16046827

Complex multi-enhancer contacts captured by Genome Architecture Mapping (GAM)

PubMed Central

Beagrie, Robert A.; Scialdone, Antonio; Schueler, Markus; Kraemer, Dorothee C.A.; Chotalia, Mita; Xie, Sheila Q.; Barbieri, Mariano; de Santiago, Inês; Lavitas, Liron-Mark; Branco, Miguel R.; Fraser, James; Dostie, Josée; Game, Laurence; Dillon, Niall; Edwards, Paul A.W.; Nicodemi, Mario; Pombo, Ana

2017-01-01

Summary The organization of the genome in the nucleus and the interactions of genes with their regulatory elements are key features of transcriptional control and their disruption can cause disease. We developed a novel genome-wide method, Genome Architecture Mapping (GAM), for measuring chromatin contacts, and other features of three-dimensional chromatin topology, based on sequencing DNA from a large collection of thin nuclear sections. We apply GAM to mouse embryonic stem cells and identify an enrichment for specific interactions between active genes and enhancers across very large genomic distances, using a mathematical model ‘SLICE’ (Statistical Inference of Co-segregation). GAM also reveals an abundance of three-way contacts genome-wide, especially between regions that are highly transcribed or contain super-enhancers, highlighting a previously inaccessible complexity in genome architecture and a major role for gene-expression specific contacts in organizing the genome in mammalian nuclei. PMID:28273065

Making connections: Insulators organize eukaryotic chromosomes into independent cis-regulatory networks

PubMed Central

Chetverina, Darya; Aoki, Tsutomu; Erokhin, Maksim; Georgiev, Pavel; Schedl, Paul

2015-01-01

Summary Insulators play a central role in subdividing the chromosome into a series of discrete topologically independent domains and in ensuring that enhancers and silencers contact their appropriate target genes. In this review we first discuss the general characteristics of insulator elements and their associated protein factors. A growing collection of insulator proteins have been identified including a family of proteins whose expression is developmental regulator. We next consider several unexpected discoveries that require us to completely rethink both how insulators function (and how they can best be assayed). These discoveries also require a reevaluation of how insulators might restrict or orchestrate (by preventing or promoting) interactions between regulatory elements and their target genes. We conclude by connecting these new insights into the mechanisms of insulator action to dynamic changes in the 3-dimensional topology of the chromatin fiber and the generation of specific patterns of gene activity during development and differentiation. PMID:24277632

Multi-Dimensional Prioritization of Dental Caries Candidate Genes and Its Enriched Dense Network Modules

PubMed Central

Wang, Quan; Jia, Peilin; Cuenco, Karen T.; Feingold, Eleanor; Marazita, Mary L.; Wang, Lily; Zhao, Zhongming

2013-01-01

A number of genetic studies have suggested numerous susceptibility genes for dental caries over the past decade with few definite conclusions. The rapid accumulation of relevant information, along with the complex architecture of the disease, provides a challenging but also unique opportunity to review and integrate the heterogeneous data for follow-up validation and exploration. In this study, we collected and curated candidate genes from four major categories: association studies, linkage scans, gene expression analyses, and literature mining. Candidate genes were prioritized according to the magnitude of evidence related to dental caries. We then searched for dense modules enriched with the prioritized candidate genes through their protein-protein interactions (PPIs). We identified 23 modules comprising of 53 genes. Functional analyses of these 53 genes revealed three major clusters: cytokine network relevant genes, matrix metalloproteinases (MMPs) family, and transforming growth factor-beta (TGF-β) family, all of which have been previously implicated to play important roles in tooth development and carious lesions. Through our extensive data collection and an integrative application of gene prioritization and PPI network analyses, we built a dental caries-specific sub-network for the first time. Our study provided insights into the molecular mechanisms underlying dental caries. The framework we proposed in this work can be applied to other complex diseases. PMID:24146904

A small molecule-based strategy for endothelial differentiation and three-dimensional morphogenesis from human embryonic stem cells.

PubMed

Geng, Yijie; Feng, Bradley

2016-07-01

The emerging models of human embryonic stem cell (hESC) self-organizing organoids provide a valuable in vitro platform for studying self-organizing processes that presumably mimic in vivo human developmental events. Here we report that through a chemical screen, we identified two novel and structurally similar small molecules BIR1 and BIR2 which robustly induced the self-organization of a balloon-shaped three-dimensional structure when applied to two-dimensional adherent hESC cultures in the absence of growth factors. Gene expression analyses and functional assays demonstrated an endothelial identity of this balloon-like structure, while cell surface marker analyses revealed a VE-cadherin(+)CD31(+)CD34(+)KDR(+)CD43(-) putative endothelial progenitor population. Furthermore, molecular marker labeling and morphological examinations characterized several other distinct DiI-Ac-LDL(+) multi-cellular modules and a VEGFR3(+) sprouting structure in the balloon cultures that likely represented intermediate structures of balloon-formation.

Robust and Efficient Biomolecular Clustering of Tumor Based on ${p}$ -Norm Singular Value Decomposition.

PubMed

Kong, Xiang-Zhen; Liu, Jin-Xing; Zheng, Chun-Hou; Hou, Mi-Xiao; Wang, Juan

2017-07-01

High dimensionality has become a typical feature of biomolecular data. In this paper, a novel dimension reduction method named p-norm singular value decomposition (PSVD) is proposed to seek the low-rank approximation matrix to the biomolecular data. To enhance the robustness to outliers, the Lp-norm is taken as the error function and the Schatten p-norm is used as the regularization function in the optimization model. To evaluate the performance of PSVD, the Kmeans clustering method is then employed for tumor clustering based on the low-rank approximation matrix. Extensive experiments are carried out on five gene expression data sets including two benchmark data sets and three higher dimensional data sets from the cancer genome atlas. The experimental results demonstrate that the PSVD-based method outperforms many existing methods. Especially, it is experimentally proved that the proposed method is more efficient for processing higher dimensional data with good robustness, stability, and superior time performance.

HDBStat!: a platform-independent software suite for statistical analysis of high dimensional biology data.

PubMed

Trivedi, Prinal; Edwards, Jode W; Wang, Jelai; Gadbury, Gary L; Srinivasasainagendra, Vinodh; Zakharkin, Stanislav O; Kim, Kyoungmi; Mehta, Tapan; Brand, Jacob P L; Patki, Amit; Page, Grier P; Allison, David B

2005-04-06

Many efforts in microarray data analysis are focused on providing tools and methods for the qualitative analysis of microarray data. HDBStat! (High-Dimensional Biology-Statistics) is a software package designed for analysis of high dimensional biology data such as microarray data. It was initially developed for the analysis of microarray gene expression data, but it can also be used for some applications in proteomics and other aspects of genomics. HDBStat! provides statisticians and biologists a flexible and easy-to-use interface to analyze complex microarray data using a variety of methods for data preprocessing, quality control analysis and hypothesis testing. Results generated from data preprocessing methods, quality control analysis and hypothesis testing methods are output in the form of Excel CSV tables, graphs and an Html report summarizing data analysis. HDBStat! is a platform-independent software that is freely available to academic institutions and non-profit organizations. It can be downloaded from our website http://www.soph.uab.edu/ssg_content.asp?id=1164.

Long-depth imaging of specific gene expressions in whole-mount mouse embryos with single-photon excitation confocal fluorescence microscopy and FISH.

PubMed

Palmes-Saloma, C; Saloma, C

2000-07-01

Long-depth imaging of specific gene expression in the midgestation whole-mount mouse embryo (WME) is demonstrated with single-photon excitation (1PE) confocal fluorescence microscopy and fluorescence in situ hybridization. Expression domains of Pax-6 mRNA transcripts were labeled with an in situ hybridization probe that is a RNA sequence complementary to the cloned gene fragment and were rendered visible using two fluorochrome-conjugated antibodies that fluoresce at peak wavelengths of lambda(F) = 0.525 microm and lambda(F) = 0. 580 microm, respectively. Distributions of Pax-6 mRNA domains as deep as 1000 microm in the day 9.5 WME were imaged with a long-working-distance (13.6 mm) objective lens (magnification 5x). The scattering problem posed by the optically thick WME sample is alleviated by careful control of the detector pinhole size and the application of simple but fast postdetection image enhancement techniques, such as space and wavelength averaging to produce high-quality fluorescence images. A three-dimensional reconstruction that clearly shows the Pax-6 mRNA expression domains in the forebrain, diencephalon, optic cup, and spinal cord of the day 9.5 WME is obtained. The advantages of 1PE confocal fluorescence imaging over two-photon excitation fluorescence imaging are discussed for the case of long-depth imaging in highly scattering media. Imaging in midgestation WMEs at optical depths of more than 350 microm has not yet been realized with two-photon fluorescence excitation. Copyright 2000 Academic Press.

Transfer of chromosome 3 fragments suppresses tumorigenicity of an ovarian cancer cell line monoallelic for chromosome 3p.

PubMed

Cody, N A L; Ouellet, V; Manderson, E N; Quinn, M C J; Filali-Mouhim, A; Tellis, P; Zietarska, M; Provencher, D M; Mes-Masson, A-M; Chevrette, M; Tonin, P N

2007-01-25

Multiple chromosome 3p tumor suppressor genes (TSG) have been proposed in the pathogenesis of ovarian cancer based on complex patterns of 3p loss. To attain functional evidence in support of TSGs and identify candidate regions, we applied a chromosome transfer method involving cell fusions of the tumorigenic OV90 human ovarian cancer cell line, monoallelic for 3p and an irradiated mouse cell line containing a human chromosome 3 in order to derive OV90 hybrids containing normal 3p fragments. The resulting hybrids showed complete or incomplete suppression of tumorigenicity in nude mouse xenograft assays, and varied in their ability to form colonies in soft agarose and three-dimensional spheroids in a manner consistent with alteration of their in vivo tumorigenic phenotypes. Expression microarray analysis identified a set of common differentially expressed genes, such as SPARC, DAB2 and VEGF, some of which have been shown implicated in ovarian cancer. Genotyping assays revealed that they harbored normal 3p fragments, some of which overlapped candidate TSG regions (3p25-p26, 3p24 and 3p14-pcen) identified previously in loss of heterozygosity analyses of ovarian cancers. However, only the 3p12-pcen region was acquired in common by all hybrids where expression microarray analysis identified differentially expressed genes. The correlation of 3p12-pcen transfer and tumor suppression with a concerted re-programming of the cellular transcriptome suggest that the putative TSG may have affected key underlying events in ovarian cancer.

Changes in gene expression in macrophages infected with Mycobacterium tuberculosis: a combined transcriptomic and proteomic approach

PubMed Central

Ragno, Silvia; Romano, Maria; Howell, Steven; Pappin, Darryl J C; Jenner, Peter J; Colston, Michael J

2001-01-01

We investigated the changes which occur in gene expression in the human macrophage cell line, THP1, at 1, 6 and 12 hr following infection with Mycobacterium tuberculosis. The analysis was carried out at the transcriptome level, using microarrays consisting of 375 human genes generally thought to be involved in immunoregulation, and at the proteomic level, using two-dimensional gel electrophoresis and mass spectrometry. The analysis of the transcriptome using microarrays revealed that many genes were up-regulated at 6 and 12 hr. Most of these genes encoded proteins involved in cell migration and homing, including the chemokines interleukin (IL)-8, osteopontin, monocyte chemotactic protein-1 (MCP-1), macrophage inflammatory protein-1α (MIP-1α), regulated on activation, normal, T-cell expressed and secreted (RANTES), MIP-1β, MIP-3α, myeloid progenitor inhibitory factor-1 (MPIF-1), pulmonary and activation regulated chemokine (PARC), growth regulated gene-β (GRO-β), GRO-γ, MCP-2, I-309, and the T helper 2 (Th2) and eosinophil-attracting chemokine, eotaxin. Other genes involved in cell migration which were up-regulated included the matrix metalloproteinase MMP-9, vascular endothelial growth factor (VEGF) and its receptor Flk-1, the chemokine receptor CCR3, and the cell adhesion molecules vesicular cell adhesion molecule-1 (VCAM-1) and integrin a3. In addition to the chemokine response, genes encoding the proinflammatory cytokines IL-1β (showing a 433-fold induction), IL-2 and tumour necrosis factor-α (TNF-α), were also found to be induced at 6 and/or 12 hr. It was more difficult to detect changes using the proteomic approach. Nevertheless, IL-1β was again shown to be strongly up-regulated. The enzyme manganese superoxide dismutase was also found to be strongly up-regulated; this enzyme was found to be macrophage-, rather than M. tuberculosis, derived. The heat-shock protein hsp27 was found to be down-regulated following infection. We also identified a mycobacterial protein, the product of the atpD gene (thought to be involved in the regulation of cytoplasmic pH) in the infected macrophage extracts. PMID:11576227

Linking Automated Data Analysis and Visualization with Applications in Developmental Biology and High-Energy Physics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ruebel, Oliver

2009-11-20

Knowledge discovery from large and complex collections of today's scientific datasets is a challenging task. With the ability to measure and simulate more processes at increasingly finer spatial and temporal scales, the increasing number of data dimensions and data objects is presenting tremendous challenges for data analysis and effective data exploration methods and tools. Researchers are overwhelmed with data and standard tools are often insufficient to enable effective data analysis and knowledge discovery. The main objective of this thesis is to provide important new capabilities to accelerate scientific knowledge discovery form large, complex, and multivariate scientific data. The research coveredmore » in this thesis addresses these scientific challenges using a combination of scientific visualization, information visualization, automated data analysis, and other enabling technologies, such as efficient data management. The effectiveness of the proposed analysis methods is demonstrated via applications in two distinct scientific research fields, namely developmental biology and high-energy physics.Advances in microscopy, image analysis, and embryo registration enable for the first time measurement of gene expression at cellular resolution for entire organisms. Analysis of high-dimensional spatial gene expression datasets is a challenging task. By integrating data clustering and visualization, analysis of complex, time-varying, spatial gene expression patterns and their formation becomes possible. The analysis framework MATLAB and the visualization have been integrated, making advanced analysis tools accessible to biologist and enabling bioinformatic researchers to directly integrate their analysis with the visualization. Laser wakefield particle accelerators (LWFAs) promise to be a new compact source of high-energy particles and radiation, with wide applications ranging from medicine to physics. To gain insight into the complex physical processes of particle acceleration, physicists model LWFAs computationally. The datasets produced by LWFA simulations are (i) extremely large, (ii) of varying spatial and temporal resolution, (iii) heterogeneous, and (iv) high-dimensional, making analysis and knowledge discovery from complex LWFA simulation data a challenging task. To address these challenges this thesis describes the integration of the visualization system VisIt and the state-of-the-art index/query system FastBit, enabling interactive visual exploration of extremely large three-dimensional particle datasets. Researchers are especially interested in beams of high-energy particles formed during the course of a simulation. This thesis describes novel methods for automatic detection and analysis of particle beams enabling a more accurate and efficient data analysis process. By integrating these automated analysis methods with visualization, this research enables more accurate, efficient, and effective analysis of LWFA simulation data than previously possible.« less

Uncaria rhynchophylla upregulates the expression of MIF and cyclophilin A in kainic acid-induced epilepsy rats: A proteomic analysis.

PubMed

Lo, Wan-Yu; Tsai, Fuu-Jen; Liu, Chung-Hsiang; Tang, Nou-Ying; Su, Shan-Yu; Lin, Shinn-Zong; Chen, Chun-Chung; Shyu, Woei-Cherng; Hsieh, Ching-Liang

2010-01-01

Uncaria rhynchophylla (Miq) Jack (UR) is a traditional Chinese herb and is used for the treatment of convulsive disorders, including epilepsy. Our previous study has shown that UR, as well as its major component rhynchophylline (RH), has an anticonvulsive effect and this effect is closely related to its scavenging activities of oxygen free radicals. The purpose of the present study was to investigate the effect of (UR) on the expression of proteins using a proteomics analysis in Sprague-Dawley (SD) rats with kainic acid (KA)-induced epileptic seizures. We profiled the differentially expressed proteins on two-dimensional electrophoresis (2-DE) maps derived from the frontal cortex and hippocampus of rat brain tissue 24 hours after KA-induced epileptic seizures. The results indicated that macrophage migration inhibitory factor (MIF) and cyclophilin A were under expressed in frontal cortex by an average of 0.19- and 0.23-fold, respectively. In the frontal cortex, MIF and cyclophilin A were significantly decreased in the KA group and these decreases were confirmed by the Western blots. However, in the hippocampus, only cyclophilin A was significantly decreased in the KA group. In addition, in real-time quantitative PCR (Q-PCR), MIF and cyclophilin A gene expressions were also significantly under expressed in the frontal cortex, and only the cyclophilin A gene was also significantly under expressed in the hippocampus in the KA group. These under expressions of MIF and cyclophilin A could be overcome by the treatment of UR and RH. In conclusion, the under expressions of MIF and cyclophilin A in the frontal cortex and hippocampus in KA-treated rats, which were overcome by both UR and UH treatment, suggesting that both MIF and cyclophilin A at least partly participate in the anticonvulsive effect of UR.

Kaposi's Sarcoma-Associated Herpesvirus Hijacks RNA Polymerase II To Create a Viral Transcriptional Factory

PubMed Central

Chen, Christopher Phillip; Lyu, Yuanzhi; Chuang, Frank; Nakano, Kazushi; Izumiya, Chie; Jin, Di; Campbell, Mel

2017-01-01

ABSTRACT Locally concentrated nuclear factors ensure efficient binding to DNA templates, facilitating RNA polymerase II recruitment and frequent reutilization of stable preinitiation complexes. We have uncovered a mechanism for effective viral transcription by focal assembly of RNA polymerase II around Kaposi's sarcoma-associated herpesvirus (KSHV) genomes in the host cell nucleus. Using immunofluorescence labeling of latent nuclear antigen (LANA) protein, together with fluorescence in situ RNA hybridization (RNA-FISH) of the intron region of immediate early transcripts, we visualized active transcription of viral genomes in naturally infected cells. At the single-cell level, we found that not all episomes were uniformly transcribed following reactivation stimuli. However, those episomes that were being transcribed would spontaneously aggregate to form transcriptional “factories,” which recruited a significant fraction of cellular RNA polymerase II. Focal assembly of “viral transcriptional factories” decreased the pool of cellular RNA polymerase II available for cellular gene transcription, which consequently impaired cellular gene expression globally, with the exception of selected ones. The viral transcriptional factories localized with replicating viral genomic DNAs. The observed colocalization of viral transcriptional factories with replicating viral genomic DNA suggests that KSHV assembles an “all-in-one” factory for both gene transcription and DNA replication. We propose that the assembly of RNA polymerase II around viral episomes in the nucleus may be a previously unexplored aspect of KSHV gene regulation by confiscation of a limited supply of RNA polymerase II in infected cells. IMPORTANCE B cells infected with Kaposi's sarcoma-associated herpesvirus (KSHV) harbor multiple copies of the KSHV genome in the form of episomes. Three-dimensional imaging of viral gene expression in the nucleus allows us to study interactions and changes in the physical distribution of these episomes following stimulation. The results showed heterogeneity in the responses of individual KSHV episomes to stimuli within a single reactivating cell; those episomes that did respond to stimulation, aggregated within large domains that appear to function as viral transcription factories. A significant portion of cellular RNA polymerase II was trapped in these factories and served to transcribe viral genomes, which coincided with an overall decrease in cellular gene expression. Our findings uncover a strategy of KSHV gene regulation through focal assembly of KSHV episomes and a molecular mechanism of late gene expression. PMID:28331082

CSAX: Characterizing Systematic Anomalies in eXpression Data

PubMed Central

Noto, Keith; Majidi, Saeed; Edlow, Andrea G.; Wick, Heather C.; Bianchi, Diana W.

2015-01-01

Abstract Methods for translating gene expression signatures into clinically relevant information have typically relied upon having many samples from patients with similar molecular phenotypes. Here, we address the question of what can be done when it is relatively easy to obtain healthy patient samples, but when abnormalities corresponding to disease states may be rare and one-of-a-kind. The associated computational challenge, anomaly detection, is a well-studied machine-learning problem. However, due to the dimensionality and variability of expression data, existing methods based on feature space analysis or individual anomalously expressed genes are insufficient. We present a novel approach, CSAX, that identifies pathways in an individual sample in which the normal expression relationships are disrupted. To evaluate our approach, we have compiled and released a compendium of public expression data sets, reformulated to create a test bed for anomaly detection. We demonstrate the accuracy of CSAX on the data sets in our compendium, compare it to other leading methods, and show that CSAX aids in both identifying anomalies and explaining their underlying biology. We describe an approach to characterizing the difficulty of specific expression anomaly detection tasks. We then illustrate CSAX's value in two developmental case studies. Confirming prior hypotheses, CSAX highlights disruption of platelet activation pathways in a neonate with retinopathy of prematurity and identifies, for the first time, dysregulated oxidative stress response in second trimester amniotic fluid of fetuses with obese mothers. Our approach provides an important step toward identification of individual disease patterns in the era of precision medicine. PMID:25651392

Molecular cloning and expression of a gene that controls the high-temperature regulon of Escherichia coli.

PubMed Central

Neidhardt, F C; VanBogelen, R A; Lau, E T

1983-01-01

The high-temperature production (HTP) regulon of Escherichia coli consists of a set of operons that are induced coordinately by a shift to a high temperature under the control of a single chromosomal gene called htpR or hin. To identify more components of this regulon, the rates of synthesis of many polypeptides resolved on two-dimensional polyacrylamide gels were measured in various strains by pulse-labeling after a temperature shift-up. A total of 13 polypeptides were found to be heat inducible only in cells bearing a normal htpR gene on the chromosome or on a plasmid; on this basis these polypeptides were designated products of the HTP regulon. Several hybrid plasmids that contain segments of the E. coli chromosome in the 75-min region were found to carry the htpR gene. A restriction map of this region was constructed, and selected fragments were subcloned and tested for the ability to complement an htpR mutant. The polypeptides encoded by these fragments were detected by permitting expression in maxicells, minicells, and chloramphenicol-treated cells. Complementation was accompanied by production of a polypeptide having a molecular weight of approximately 33,000. This polypeptide, designated F33.4, was markedly reduced in amount in an htpR mutant expected to contain very little htpR gene product. Polypeptide F33.4 is postulated to be the product of htpR and to be an effector that controls heat induction of the HTP regulon. Images PMID:6337122

EPS-LASSO: Test for High-Dimensional Regression Under Extreme Phenotype Sampling of Continuous Traits.

PubMed

Xu, Chao; Fang, Jian; Shen, Hui; Wang, Yu-Ping; Deng, Hong-Wen

2018-01-25

Extreme phenotype sampling (EPS) is a broadly-used design to identify candidate genetic factors contributing to the variation of quantitative traits. By enriching the signals in extreme phenotypic samples, EPS can boost the association power compared to random sampling. Most existing statistical methods for EPS examine the genetic factors individually, despite many quantitative traits have multiple genetic factors underlying their variation. It is desirable to model the joint effects of genetic factors, which may increase the power and identify novel quantitative trait loci under EPS. The joint analysis of genetic data in high-dimensional situations requires specialized techniques, e.g., the least absolute shrinkage and selection operator (LASSO). Although there are extensive research and application related to LASSO, the statistical inference and testing for the sparse model under EPS remain unknown. We propose a novel sparse model (EPS-LASSO) with hypothesis test for high-dimensional regression under EPS based on a decorrelated score function. The comprehensive simulation shows EPS-LASSO outperforms existing methods with stable type I error and FDR control. EPS-LASSO can provide a consistent power for both low- and high-dimensional situations compared with the other methods dealing with high-dimensional situations. The power of EPS-LASSO is close to other low-dimensional methods when the causal effect sizes are small and is superior when the effects are large. Applying EPS-LASSO to a transcriptome-wide gene expression study for obesity reveals 10 significant body mass index associated genes. Our results indicate that EPS-LASSO is an effective method for EPS data analysis, which can account for correlated predictors. The source code is available at https://github.com/xu1912/EPSLASSO. hdeng2@tulane.edu. Supplementary data are available at Bioinformatics online. © The Author (2018). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

A Comparative Study on Multifactor Dimensionality Reduction Methods for Detecting Gene-Gene Interactions with the Survival Phenotype

PubMed Central

Lee, Seungyeoun; Kim, Yongkang; Kwon, Min-Seok; Park, Taesung

2015-01-01

Genome-wide association studies (GWAS) have extensively analyzed single SNP effects on a wide variety of common and complex diseases and found many genetic variants associated with diseases. However, there is still a large portion of the genetic variants left unexplained. This missing heritability problem might be due to the analytical strategy that limits analyses to only single SNPs. One of possible approaches to the missing heritability problem is to consider identifying multi-SNP effects or gene-gene interactions. The multifactor dimensionality reduction method has been widely used to detect gene-gene interactions based on the constructive induction by classifying high-dimensional genotype combinations into one-dimensional variable with two attributes of high risk and low risk for the case-control study. Many modifications of MDR have been proposed and also extended to the survival phenotype. In this study, we propose several extensions of MDR for the survival phenotype and compare the proposed extensions with earlier MDR through comprehensive simulation studies. PMID:26339630

Enzymatic improvement of mitochondrial thiol oxidase Erv1 for oxidized glutathione fermentation by Saccharomyces cerevisiae.

PubMed

Kobayashi, Jyumpei; Sasaki, Daisuke; Hara, Kiyotaka Y; Hasunuma, Tomohisa; Kondo, Akihiko

2017-03-15

Oxidized glutathione (GSSG) is the preferred form for industrial mass production of glutathione due to its high stability compared with reduced glutathione (GSH). In our previous study, over-expression of the mitochondrial thiol oxidase ERV1 gene was the most effective for high GSSG production in Saccharomyces cerevisiae cells among three types of different thiol oxidase genes. We improved Erv1 enzyme activity for oxidation of GSH and revealed that S32 and N34 residues are critical for the oxidation. Five engineered Erv1 variant proteins containing S32 and/or N34 replacements exhibited 1.7- to 2.4-fold higher in vitro GSH oxidation activity than that of parental Erv1, whereas the oxidation activities of these variants for γ-glutamylcysteine were comparable. According to three-dimensional structures of Erv1 and protein stability assays, S32 and N34 residues interact with nearby residues through hydrogen bonding and greatly contribute to protein stability. These results suggest that increased flexibility by amino acid replacements around the active center decrease inhibitory effects on GSH oxidation. Over-expressions of mutant genes coding these Erv1 variants also increased GSSG and consequently total glutathione production in S. cerevisiae cells. Over-expression of the ERV1 S32A gene was the most effective for GSSG production in S. cerevisiae cells among the parent and other mutant genes, and it increased GSSG production about 1.5-fold compared to that of the parental ERV1 gene. This is the first study demonstrating the pivotal effects of S32 and N34 residues to high GSH oxidation activity of Erv1. Furthermore, in vivo validity of Erv1 variants containing these S32 and N34 replacements were also demonstrated. This study indicates potentials of Erv1 for high GSSG production.

The Phenazine 2-Hydroxy-Phenazine-1-Carboxylic Acid Promotes Extracellular DNA Release and Has Broad Transcriptomic Consequences in Pseudomonas chlororaphis 30–84

DOE PAGES

Wang, Dongping; Yu, Jun Myoung; Dorosky, Robert J.; ...

2016-01-26

Enhanced production of 2-hydroxy-phenazine-1-carboxylic acid (2-OH-PCA) by the biological control strain Pseudomonas chlororaphis 30–84 derivative 30-84O* was shown previously to promote cell adhesion and alter the three-dimensional structure of surfaceattached biofilms compared to the wild type. The current study demonstrates that production of 2-OH-PCA promotes the release of extracellular DNA, which is correlated with the production of structured biofilm matrix. Moreover, the essential role of the extracellular DNA in maintaining the mass and structure of the 30–84 biofilm matrix is demonstrated. To better understand the role of different phenazines in biofilm matrix production and gene expression, transcriptomic analyses were conductedmore » comparing gene expression patterns of populations of wild type, 30-84O* and a derivative of 30–84 producing only PCA (30-84PCA) to a phenazine defective mutant (30-84ZN) when grown in static cultures. RNA-Seq analyses identified a group of 802 genes that were differentially expressed by the phenazine producing derivatives compared to 30-84ZN, including 240 genes shared by the two 2-OH-PCA producing derivatives, the wild type and 30-84O*. A gene cluster encoding a bacteriophage- derived pyocin and its lysis cassette was upregulated in 2-OH-PCA producing derivatives. A holin encoded in this gene cluster was found to contribute to the release of eDNA in 30–84 biofilm matrices, demonstrating that the influence of 2-OH-PCA on eDNA production is due in part to cell autolysis as a result of pyocin production and release. The results expand the current understanding of the functions different phenazines play in the survival of bacteria in biofilm-forming communities.« less

The Phenazine 2-Hydroxy-Phenazine-1-Carboxylic Acid Promotes Extracellular DNA Release and Has Broad Transcriptomic Consequences in Pseudomonas chlororaphis 30–84

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Dongping; Yu, Jun Myoung; Dorosky, Robert J.

Enhanced production of 2-hydroxy-phenazine-1-carboxylic acid (2-OH-PCA) by the biological control strain Pseudomonas chlororaphis 30–84 derivative 30-84O* was shown previously to promote cell adhesion and alter the three-dimensional structure of surfaceattached biofilms compared to the wild type. The current study demonstrates that production of 2-OH-PCA promotes the release of extracellular DNA, which is correlated with the production of structured biofilm matrix. Moreover, the essential role of the extracellular DNA in maintaining the mass and structure of the 30–84 biofilm matrix is demonstrated. To better understand the role of different phenazines in biofilm matrix production and gene expression, transcriptomic analyses were conductedmore » comparing gene expression patterns of populations of wild type, 30-84O* and a derivative of 30–84 producing only PCA (30-84PCA) to a phenazine defective mutant (30-84ZN) when grown in static cultures. RNA-Seq analyses identified a group of 802 genes that were differentially expressed by the phenazine producing derivatives compared to 30-84ZN, including 240 genes shared by the two 2-OH-PCA producing derivatives, the wild type and 30-84O*. A gene cluster encoding a bacteriophage- derived pyocin and its lysis cassette was upregulated in 2-OH-PCA producing derivatives. A holin encoded in this gene cluster was found to contribute to the release of eDNA in 30–84 biofilm matrices, demonstrating that the influence of 2-OH-PCA on eDNA production is due in part to cell autolysis as a result of pyocin production and release. The results expand the current understanding of the functions different phenazines play in the survival of bacteria in biofilm-forming communities.« less

The Phenazine 2-Hydroxy-Phenazine-1-Carboxylic Acid Promotes Extracellular DNA Release and Has Broad Transcriptomic Consequences in Pseudomonas chlororaphis 30–84

PubMed Central

Wang, Dongping; Yu, Jun Myoung; Dorosky, Robert J.; Pierson, Leland S.; Pierson, Elizabeth A.

2016-01-01

Enhanced production of 2-hydroxy-phenazine-1-carboxylic acid (2-OH-PCA) by the biological control strain Pseudomonas chlororaphis 30–84 derivative 30-84O* was shown previously to promote cell adhesion and alter the three-dimensional structure of surface-attached biofilms compared to the wild type. The current study demonstrates that production of 2-OH-PCA promotes the release of extracellular DNA, which is correlated with the production of structured biofilm matrix. Moreover, the essential role of the extracellular DNA in maintaining the mass and structure of the 30–84 biofilm matrix is demonstrated. To better understand the role of different phenazines in biofilm matrix production and gene expression, transcriptomic analyses were conducted comparing gene expression patterns of populations of wild type, 30-84O* and a derivative of 30–84 producing only PCA (30-84PCA) to a phenazine defective mutant (30-84ZN) when grown in static cultures. RNA-Seq analyses identified a group of 802 genes that were differentially expressed by the phenazine producing derivatives compared to 30-84ZN, including 240 genes shared by the two 2-OH-PCA producing derivatives, the wild type and 30-84O*. A gene cluster encoding a bacteriophage-derived pyocin and its lysis cassette was upregulated in 2-OH-PCA producing derivatives. A holin encoded in this gene cluster was found to contribute to the release of eDNA in 30–84 biofilm matrices, demonstrating that the influence of 2-OH-PCA on eDNA production is due in part to cell autolysis as a result of pyocin production and release. The results expand the current understanding of the functions different phenazines play in the survival of bacteria in biofilm-forming communities. PMID:26812402

[Vestibular compensation studies]. [Vestibular Compensation and Morphological Studies

NASA Technical Reports Server (NTRS)

Perachio, Adrian A. (Principal Investigator)

1996-01-01

The following topics are reported: neurophysiological studies on MVN neurons during vestibular compensation; effects of spinal cord lesions on VNC neurons during compensation; a closed-loop vestibular compensation model for horizontally canal-related MVN neurons; spatiotemporal convergence in VNC neurons; contributions of irregularly firing vestibular afferents to linear and angular VOR's; application to flight studies; metabolic measures in vestibular neurons; immediate early gene expression following vestibular stimulation; morphological studies on primary afferents, central vestibular pathways, vestibular efferent projection to the vestibular end organs, and three-dimensional morphometry and imaging.

Modeling the Activity of Single Genes

NASA Technical Reports Server (NTRS)

Mjolsness, Eric; Gibson, Michael

1999-01-01

The central dogma of molecular biology states that information is stored in DNA, transcribed to messenger RNA (mRNA) and then translated into proteins. This picture is significantly augmentated when we consider the action of certain proteins in regulating transcription. These transcription factors provide a feedback pathway by which genes can regulate one another's expression as mRNA and then as protein. To review: DNA, RNA and proteins have different functions. DNA is the molecular storehouse of genetic information. When cells divide, the DNA is replicated, so that each daughter cell maintains the same genetic information as the mother cell. RNA acts as a go-between from DNA to proteins. Only a single copy of DNA is present, but multiple copies of the same piece of RNA may be present, allowing cells to make huge amounts of protein. In eukaryotes (organisms with a nucleus), DNA is found in the nucleus only. RNA is copied in the nucleus then translocates(moves) outside the nucleus, where it is transcribed into proteins. Along the way, the RNA may be spliced, i.e., may have pieces cut out. RNA then attaches to ribosomes and is translated to proteins. Proteins are the machinery of the cell other than DNA and RNA, all the complex molecules of the cell are proteins. Proteins are specialized machines, each of which fulfills its own task, which may be transporting oxygen, catalyzing reactions, or responding to extracellular signals, just to name a few. One of the more interesting functions a protein may have is binding directly or indirectly to DNA to perform transcriptional regulation, thus forming a closed feedback loop of gene regulation. The structure of DNA and the central dogma were understood in the 50s; in the early 80s it became possible to make arbitrary modifications to DNA and use cellular machinery to transcribe and translate the resulting genes; more recently, genomes (i.e., the complete DNA sequence) of many organisms have been sequenced. This large-scale sequencing began with simple organisms, viruses and bacteria, progressed to eukaryotes such as yeast, and more recently (1998) progressed to a multi-cellular animal, the nematode Caenorhabditis elegans. Sequencers have now moved on to the fruit fly Drosophila melanogaster, whose sequence is slated for completion by the end of 1999. The human genome project is expected to determine the complete sequence of all 3 billion bases of human DNA within the next five years. In the wake of genome-scale sequencing, further instrumentation is being developed to assay gene expression and function on a comparably large scale. Much of the work in computational biology focuses on computational tools used in sequencing, finding genes that are related to a particular gene, finding which parts of the DNA code for proteins and which do not, understanding what proteins will be formed from a given length of DNA, predicting how the proteins will fold from a one-dimensional structure into a three dimensional structure, and so on. Much less computational work has been done regarding the function of proteins. One reason for this is that different proteins function very differently, and so work on protein function is very specific to certain classes of proteins. There are, for example, proteins such enzymes that catalyze various intracellular reactions, receptors that respond to extracellular signals and ion channels that regulate the flow of charged particles into and out of the cell. In this chapter, we will consider a particular class of proteins called transcription factors(TFs), which are responsible for regulating when a certain gene is expressed in a certain cell, which cells it is express in, and how much is expressed. Understanding these processes will involve developing a deeper understanding of transcription, translation, and the cellular processes that control those processes. All of these elements fall under the aegis of gene regulation or more narrowly transcriptional regulation. Some of the key questions in gene regulation are: What genes are expressed in a certain cell at a certain time? How does gene expression differ from cell to cell in a multicellular organism? Which proteins act as transcription factors, i.e., are important in regulating gene expression? From questions like these, we hope to understand which genes are important for various macroscopic processes. Nearly all of the cells of a multicellular organism contain the same DNA. Yet this same genetic information yields a large number of different cell types. The fundamental difference between a neuron and a liver cell, for example, is which genes are expressed. Thus understanding gene regulation is an important step in understanding development. Furthermore, understanding the usual genes that are expressed in cells may give important clues about various diseases. Some diseases, such as sickle cell anemia and cystic fibrosis, are caused by defects in single, non-regulatory genes; others, such as certain cancers, are caused when the cellular control circuitry malfunctions - an understanding of these diseases will involve pathways of multiple interacting gene products. There are numerous challenges in the area of understanding and modeling gene regulation. First and foremost, biologists would like to develop a deeper understanding of the processes involved, including which genes and families of genes are important, how they interact, etc. From a computation point of view, there has been embarrassingly little work done. In this chapter there are many areas in which we can phrase meaningful, non-trivial computational questions, but questions that have not been addressed. Some of these are purely computational (what is a good algorithm for dealing with a model of type X) and others are more mathematical (given a system with certain characteristics, what sort of model can one use? How does one find biochemical parameters from system-level behavior using as few experiments as possible?). In addition to biological and algorithmic problems, there is also the ever-present issue of theoretical biology - what general principles can be derived from these systems, what can one do with models other than just simulate time-courses, what can be deduced about a class of systems without knowing all the details? The fundamental challenge to computationalists and theorists is to add value to the biology - to use models, modeling techniques and algorithms to understand the biology in new ways.

Three-dimensional Myoblast Aggregates--Effects of Modeled Microgravity

NASA Technical Reports Server (NTRS)

Byerly, Diane; Sognier, M. A.; Marquette, M. L.

2006-01-01

The overall objective of these studies is to elucidate the molecular and cellular alterations that contribute to muscle atrophy in astronauts caused by exposure to microgravity conditions in space. To accomplish this, a three-dimensional model test system was developed using mouse myoblast cells (C2C12). Myoblast cells were grown as three-dimensional aggregates (without scaffolding or other solid support structures) in both modeled microgravity (Rotary Cell Culture System, Synthecon, Inc.) and at unit gravity in coated Petri dishes. Evaluation of H&E stained thin sections of the aggregates revealed the absence of any necrosis. Confocal microscopy evaluations of cells stained with the Live/Dead assay (Molecular Probes) confirmed that viable cells were present throughout the aggregates with an average of only three dead cells observed per aggregate. Preliminary results from gene array analysis (Affymetrix chip U74Av2) showed that approximately 14% of the genes were down regulated (decreased more than 3 fold) and 4% were upregulated in cells exposed to modeled microgravity for 12 hours compared to unit gravity controls. Additional studies using fluorescent phallacidin revealed a decrease in F-actin in the cells exposed to modeled microgravity compared to unit gravity. Myoblast cells grown as aggregates in modeled microgravity exhibited spontaneous differentiation into syncitia while no differentiation was seen in the unit gravity controls. These studies show that 1)the model test system developed is suitable for assessing cellular and molecular alterations in myoblasts; 2) gene expression alterations occur rapidly (within 12 hours) following exposure to modeled microgravity; and 3) modeled microgravity conditions stimulated myoblast cell differentiation. Achieving a greater understanding of the molecular alterations leading to muscle atrophy will eventually enable the development of cell-based countermeasures, which may be valuable for treatment of muscle diseases on Earth and future space explorations.

Downregulation of Connective Tissue Growth Factor by Three-Dimensional Matrix Enhances Ovarian Carcinoma Cell Invasion

PubMed Central

Barbolina, Maria V.; Adley, Brian P.; Kelly, David L.; Shepard, Jaclyn; Fought, Angela J.; Scholtens, Denise; Penzes, Peter; Shea, Lonnie D.; Sharon Stack, M

2010-01-01

Epithelial ovarian carcinoma (EOC) is a leading cause of death from gynecologic malignancy, due mainly to the prevalence of undetected metastatic disease. The process of cell invasion during intra-peritoneal anchoring of metastatic lesions requires concerted regulation of many processes, including modulation of adhesion to the extracellular matrix and localized invasion. Exploratory cDNA microarray analysis of early response genes (altered after 4 hours of 3-dimensional collagen culture) coupled with confirmatory real-time RT-PCR, multiple three-dimensional cell culture matrices, Western blot, immunostaining, adhesion, migration, and invasion assays were used to identify modulators of adhesion pertinent to EOC progression and metastasis. cDNA microarray analysis indicated a dramatic downregulation of connective tissue growth factor (CTGF) in EOC cells placed in invasion-mimicking conditions (3-dimensional type I collagen). Examination of human EOC specimens revealed that CTGF expression was absent in 46% of the tested samples (n=41), but was present in 100% of normal ovarian epithelium samples (n=7). Reduced CTGF expression occurs in many types of cells and may be a general phenomenon displayed by cells encountering a 3D environment. CTGF levels were inversely correlated with invasion such that downregulation of CTGF increased, while its upregulation reduced, collagen invasion. Cells adhered preferentially to a surface comprised of both collagen I and CTGF relative to either component alone using α6β1 and α3β1 integrins. Together these data suggest that downregulation of CTGF in EOC cells may be important for cell invasion through modulation of cell-matrix adhesion. PMID:19382180

Formation of three-dimensional fetal myocardial tissue cultures from rat for long-term cultivation.

PubMed

Just, Lothar; Kürsten, Anne; Borth-Bruhns, Thomas; Lindenmaier, Werner; Rohde, Manfred; Dittmar, Kurt; Bader, Augustinus

2006-08-01

Three-dimensional cardiomyocyte cultures offer new possibilities for the analysis of cardiac cell differentiation, spatial cellular arrangement, and time-specific gene expression in a tissue-like environment. We present a new method for generating homogenous and robust cardiomyocyte tissue cultures with good long-term viability. Ventricular heart cells prepared from fetal rats at embryonic day 13 were cultured in a scaffold-free two-step process. To optimize the cell culture model, several digestion protocols and culture conditions were tested. After digestion of fetal cardiac ventricles, the resultant cell suspension of isolated cardiocytes was shaken to initialize cell aggregate formation. In the second step, these three-dimensional cell aggregates were transferred onto a microporous membrane to allow further microstructure formation. Autonomously beating cultures possessed more than 25 cell layers and a homogenous distribution of cardiomyocytes without central necrosis after 8 weeks in vitro. The cardiomyocytes showed contractile elements, desmosomes, and gap junctions analyzed by immunohistochemistry and electron microscopy. The beat frequency could be modulated by adrenergic agonist and antagonist. Adenoviral green fluorescent protein transfer into cardiomyocytes was possible and highly effective. This three-dimensional tissue model proved to be useful for studying cell-cell interactions and cell differentiation processes in a three-dimensional cell arrangement.

Molecular effects of fractional ablative erbium:YAG laser treatment with multiple stacked pulses on standardized human three-dimensional organotypic skin models.

PubMed

Schmitt, Laurenz; Amann, P M; Marquardt, Y; Heise, R; Czaja, K; Gerber, P A; Steiner, T; Hölzle, F; Baron, Jens Malte

2017-05-01

The molecular changes in gene expression following ablative laser treatment of skin lesions, such as atrophic scars and UV-damaged skin, are not completely understood. A standardized in vitro model of human skin, to study the effects of laser treatment on human skin, has been recently developed. Therefore, the aim of the investigation was to examine morphological and molecular changes caused by fractional ablative erbium:YAG laser treatment on an in vitro full-thickness 3D standardized organotypic model of human skin. A fractional ablative erbium:YAG laser was used to irradiate organotypic human 3D models. Laser treatments were performed at four different settings using a variety of stacked pulses with similar cumulative total energy fluence (60 J/cm 2 ). Specimens were harvested at specified time points and real-time PCR (qRT-PCR) and microarray studies were performed. Frozen sections were examined histologically. Three days after erbium:YAG laser treatment, a significantly increased mRNA expression of matrix metalloproteinases and their inhibitors (MMP1, MMP2, MMP3, TIMP1, and TIMP2), chemokines (CXCL1, CXCL2, CXCL5, and CXCL6), and cytokines such as IL6, IL8, and IL24 could be detected. qRT-PCR studies confirmed the enhanced mRNA expression of IL6, IL8, IL24, CXCLs, and MMPs. In contrast, the mRNA expression of epidermal differentiation markers, such as keratin-associated protein 4, filaggrin, filaggrin 2, and loricrin, and antimicrobial peptides (S100A7A, S100A9, and S100A12) as well as CASP14, DSG2, IL18, and IL36β was reduced. Four different settings with similar cumulative doses have been tested (N10%, C10%, E10%, and W25%). These laser treatments resulted in different morphological changes and effects on gene regulations. Longer pulse durations (1000 μs) especially had the strongest impact on gene expression and resulted in an upregulation of genes, such as collagen-1A2, collagen-5A2, and collagen-6A2, as well as FGF2. Histologically, all treatment settings resulted in a complete regeneration of the epidermis 3 days after irradiation. Fractional ablative erbium:YAG laser treatment with a pulse stacking technique resulted in histological alterations and shifts in the expression of various genes related to epidermal differentiation, inflammation, and dermal remodeling depending on the treatment setting applied. A standardized in vitro 3D model of human skin proved to be a useful tool for exploring the effects of various laser settings both on skin morphology and gene expression during wound healing. It provides novel data on the gene expression and microscopic architecture of the exposed skin. This may enhance our understanding of laser treatment at a molecular level.

Antimicrobial and Virulence-Modulating Effects of Clove Essential Oil on the Foodborne Pathogen Campylobacter jejuni

PubMed Central

Kovács, Judit K.; Felső, Péter; Makszin, Lilla; Pápai, Zoltán; Horváth, Györgyi; Ábrahám, Hajnalka; Palkovics, Tamás; Böszörményi, Andrea; Emődy, Levente

2016-01-01

ABSTRACT Our study investigated the antimicrobial action of clove (Syzygium aromaticum) essential oil (EO) on the zoonotic pathogen Campylobacter jejuni. After confirming the clove essential oil's general antibacterial effect, we analyzed the reference strain Campylobacter jejuni NCTC 11168. Phenotypic, proteomic, and transcriptomic methods were used to reveal changes in cell morphology and functions when exposed to sublethal concentrations of clove EO. The normally curved cells showed markedly straightened and shrunken morphology on the scanning electron micrographs as a result of stress. Although, oxidative stress, as a generally accepted response to essential oils, was also present, the dominance of a general stress response was demonstrated by reverse transcription-PCR (RT-PCR). The results of RT-PCR and two-dimensional (2D) PAGE revealed that clove oil perturbs the expression of virulence-associated genes taking part in the synthesis of flagella, PEB1, PEB4, lipopolysaccharide (LPS), and serine protease. Loss of motility was also detected by a phenotypic test. Bioautographic analysis revealed that besides its major component, eugenol, at least four other spots of clove EO possessed bactericidal activity against C. jejuni. Our findings show that clove EO has a marked antibacterial and potential virulence-modulating effect on C. jejuni. IMPORTANCE This study demonstrates that the components of clove essential oil influence not only the expression of general stress genes but also the expression of virulence-associated genes. Based on this finding, alternative strategies can be worked on to control this important foodborne pathogen. PMID:27520816

Optimal 3D culture of primary articular chondrocytes for use in the rotating wall vessel bioreactor.

PubMed

Mellor, Liliana F; Baker, Travis L; Brown, Raquel J; Catlin, Lindsey W; Oxford, Julia Thom

2014-08-01

Reliable culturing methods for primary articular chondrocytes are essential to study the effects of loading and unloading on joint tissue at the cellular level. Due to the limited proliferation capacity of primary chondrocytes and their tendency to dedifferentiate in conventional culture conditions, long-term culturing conditions of primary chondrocytes can be challenging. The goal of this study was to develop a suspension culturing technique that not only would retain the cellular morphology, but also maintain the gene expression characteristics of primary articular chondrocytes. Three-dimensional culturing methods were compared and optimized for primary articular chondrocytes in the rotating wall vessel bioreactor, which changes the mechanical culture conditions to provide a form of suspension culture optimized for low shear and turbulence. We performed gene expression analysis and morphological characterization of cells cultured in alginate beads, Cytopore-2 microcarriers, primary monolayer culture, and passaged monolayer cultures using reverse transcription-PCR and laser scanning confocal microscopy. Primary chondrocytes grown on Cytopore-2 microcarriers maintained the phenotypical morphology and gene expression pattern observed in primary bovine articular chondrocytes, and retained these characteristics for up to 9 d. Our results provide a novel and alternative culturing technique for primary chondrocytes suitable for studies that require suspension such as those using the rotating wall vessel bioreactor. In addition, we provide an alternative culturing technique for primary chondrocytes that can impact future mechanistic studies of osteoarthritis progression, treatments for cartilage damage and repair, and cartilage tissue engineering.

The Fisher-Markov selector: fast selecting maximally separable feature subset for multiclass classification with applications to high-dimensional data.

PubMed

Cheng, Qiang; Zhou, Hongbo; Cheng, Jie

2011-06-01

Selecting features for multiclass classification is a critically important task for pattern recognition and machine learning applications. Especially challenging is selecting an optimal subset of features from high-dimensional data, which typically have many more variables than observations and contain significant noise, missing components, or outliers. Existing methods either cannot handle high-dimensional data efficiently or scalably, or can only obtain local optimum instead of global optimum. Toward the selection of the globally optimal subset of features efficiently, we introduce a new selector--which we call the Fisher-Markov selector--to identify those features that are the most useful in describing essential differences among the possible groups. In particular, in this paper we present a way to represent essential discriminating characteristics together with the sparsity as an optimization objective. With properly identified measures for the sparseness and discriminativeness in possibly high-dimensional settings, we take a systematic approach for optimizing the measures to choose the best feature subset. We use Markov random field optimization techniques to solve the formulated objective functions for simultaneous feature selection. Our results are noncombinatorial, and they can achieve the exact global optimum of the objective function for some special kernels. The method is fast; in particular, it can be linear in the number of features and quadratic in the number of observations. We apply our procedure to a variety of real-world data, including mid--dimensional optical handwritten digit data set and high-dimensional microarray gene expression data sets. The effectiveness of our method is confirmed by experimental results. In pattern recognition and from a model selection viewpoint, our procedure says that it is possible to select the most discriminating subset of variables by solving a very simple unconstrained objective function which in fact can be obtained with an explicit expression.

GEM-TREND: a web tool for gene expression data mining toward relevant network discovery

PubMed Central

Feng, Chunlai; Araki, Michihiro; Kunimoto, Ryo; Tamon, Akiko; Makiguchi, Hiroki; Niijima, Satoshi; Tsujimoto, Gozoh; Okuno, Yasushi

2009-01-01

Background DNA microarray technology provides us with a first step toward the goal of uncovering gene functions on a genomic scale. In recent years, vast amounts of gene expression data have been collected, much of which are available in public databases, such as the Gene Expression Omnibus (GEO). To date, most researchers have been manually retrieving data from databases through web browsers using accession numbers (IDs) or keywords, but gene-expression patterns are not considered when retrieving such data. The Connectivity Map was recently introduced to compare gene expression data by introducing gene-expression signatures (represented by a set of genes with up- or down-regulated labels according to their biological states) and is available as a web tool for detecting similar gene-expression signatures from a limited data set (approximately 7,000 expression profiles representing 1,309 compounds). In order to support researchers to utilize the public gene expression data more effectively, we developed a web tool for finding similar gene expression data and generating its co-expression networks from a publicly available database. Results GEM-TREND, a web tool for searching gene expression data, allows users to search data from GEO using gene-expression signatures or gene expression ratio data as a query and retrieve gene expression data by comparing gene-expression pattern between the query and GEO gene expression data. The comparison methods are based on the nonparametric, rank-based pattern matching approach of Lamb et al. (Science 2006) with the additional calculation of statistical significance. The web tool was tested using gene expression ratio data randomly extracted from the GEO and with in-house microarray data, respectively. The results validated the ability of GEM-TREND to retrieve gene expression entries biologically related to a query from GEO. For further analysis, a network visualization interface is also provided, whereby genes and gene annotations are dynamically linked to external data repositories. Conclusion GEM-TREND was developed to retrieve gene expression data by comparing query gene-expression pattern with those of GEO gene expression data. It could be a very useful resource for finding similar gene expression profiles and constructing its gene co-expression networks from a publicly available database. GEM-TREND was designed to be user-friendly and is expected to support knowledge discovery. GEM-TREND is freely available at . PMID:19728865

GEM-TREND: a web tool for gene expression data mining toward relevant network discovery.

PubMed

Feng, Chunlai; Araki, Michihiro; Kunimoto, Ryo; Tamon, Akiko; Makiguchi, Hiroki; Niijima, Satoshi; Tsujimoto, Gozoh; Okuno, Yasushi

2009-09-03

DNA microarray technology provides us with a first step toward the goal of uncovering gene functions on a genomic scale. In recent years, vast amounts of gene expression data have been collected, much of which are available in public databases, such as the Gene Expression Omnibus (GEO). To date, most researchers have been manually retrieving data from databases through web browsers using accession numbers (IDs) or keywords, but gene-expression patterns are not considered when retrieving such data. The Connectivity Map was recently introduced to compare gene expression data by introducing gene-expression signatures (represented by a set of genes with up- or down-regulated labels according to their biological states) and is available as a web tool for detecting similar gene-expression signatures from a limited data set (approximately 7,000 expression profiles representing 1,309 compounds). In order to support researchers to utilize the public gene expression data more effectively, we developed a web tool for finding similar gene expression data and generating its co-expression networks from a publicly available database. GEM-TREND, a web tool for searching gene expression data, allows users to search data from GEO using gene-expression signatures or gene expression ratio data as a query and retrieve gene expression data by comparing gene-expression pattern between the query and GEO gene expression data. The comparison methods are based on the nonparametric, rank-based pattern matching approach of Lamb et al. (Science 2006) with the additional calculation of statistical significance. The web tool was tested using gene expression ratio data randomly extracted from the GEO and with in-house microarray data, respectively. The results validated the ability of GEM-TREND to retrieve gene expression entries biologically related to a query from GEO. For further analysis, a network visualization interface is also provided, whereby genes and gene annotations are dynamically linked to external data repositories. GEM-TREND was developed to retrieve gene expression data by comparing query gene-expression pattern with those of GEO gene expression data. It could be a very useful resource for finding similar gene expression profiles and constructing its gene co-expression networks from a publicly available database. GEM-TREND was designed to be user-friendly and is expected to support knowledge discovery. GEM-TREND is freely available at http://cgs.pharm.kyoto-u.ac.jp/services/network.

Hypoxia promotes proliferation of human myogenic satellite cells: a potential benefactor in tissue engineering of skeletal muscle.

PubMed

Koning, Merel; Werker, Paul M N; van Luyn, Marja J A; Harmsen, Martin C

2011-07-01

Facial paralysis is a physically, psychologically, and socially disabling condition. Innovative treatment strategies based on regenerative medicine, in particular tissue engineering of skeletal muscle, are promising for treatment of patients with facial paralysis. The natural source for tissue-engineered muscle would be muscle stem cells, that is, human satellite cells (SC). In vivo, SC respond to hypoxic, ischemic muscle damage by activation, proliferation, differentiation to myotubes, and maturation to muscle fibers, while maintaining their reserve pool of SC. Therefore, our hypothesis is that hypoxia improves proliferation and differentiation of SC. During tissue engineering, a three-dimensional construct, or implanting SC in vivo, SC will encounter hypoxic environments. Thus, we set out to test our hypothesis on SC in vitro. During the first five passages, hypoxically cultured SC proliferated faster than their counterparts under normoxia. Moreover, also at higher passages, a switch from normoxia to hypoxia enhanced proliferation of SC. Hypoxia did not affect the expression of SC markers desmin and NCAM. However, the average surface expression per cell of NCAM was downregulated by hypoxia, and it also downregulated the gene expression of NCAM. The gene expression of the myogenic transcription factors PAX7, MYF5, and MYOD was upregulated by hypoxia. Moreover, gene expression of structural proteins α-sarcomeric actin, and myosins MYL1 and MYL3 was upregulated by hypoxia during differentiation. This indicates that hypoxia promotes a promyogenic shift in SC. Finally, Pax7 expression was not influenced by hypoxia and maintained in a subset of mononucleated cells, whereas these cells were devoid of structural muscle proteins. This suggests that during myogenesis in vitro, at least part of the SC adopt a quiescent, that is, reserve cells, phenotype. In conclusion, tissue engineering under hypoxic conditions would seem favorable in terms of myogenic proliferation, while maintaining the quiescent SC pool.

Identification of Genes and Proteins Necessary for Catabolism of Acyclic Terpenes and Leucine/Isovalerate in Pseudomonas aeruginosa

PubMed Central

Förster-Fromme, Karin; Höschle, Birgit; Mack, Christina; Bott, Michael; Armbruster, Wolfgang; Jendrossek, Dieter

2006-01-01

Geranyl-coenzyme A (CoA)-carboxylase (GCase; AtuC/AtuF) and methylcrotonyl-CoA-carboxylase (MCase; LiuB/LiuD) are characteristic enzymes of the catabolic pathway of acyclic terpenes (citronellol and geraniol) and of saturated methyl-branched compounds, such as leucine or isovalerate, respectively. Proteins encoded by two gene clusters (atuABCDEFGH and liuRABCDE) of Pseudomonas aeruginosa PAO1 were essential for acyclic terpene utilization (Atu) and for leucine and isovalerate utilization (Liu), respectively, as revealed by phenotype analysis of 10 insertion mutants, two-dimensional gel electrophoresis, determination of GCase and MCase activities, and Western blot analysis of wild-type and mutant strains. Analysis of the genome sequences of other pseudomonads (P. putida KT2440 and P. fluorescens Pf-5) revealed candidate genes for Liu proteins for both species and candidate genes for Atu proteins in P. fluorescens. This result concurred with the finding that P. fluorescens, but not P. putida, could grow on acyclic terpenes (citronellol and citronellate), while both species were able to utilize leucine and isovalerate. A regulatory gene, atuR, was identified upstream of atuABCDEFGH and negatively regulated expression of the atu gene cluster. PMID:16820476

BIOSPIDA: A Relational Database Translator for NCBI.

PubMed

Hagen, Matthew S; Lee, Eva K

2010-11-13

As the volume and availability of biological databases continue widespread growth, it has become increasingly difficult for research scientists to identify all relevant information for biological entities of interest. Details of nucleotide sequences, gene expression, molecular interactions, and three-dimensional structures are maintained across many different databases. To retrieve all necessary information requires an integrated system that can query multiple databases with minimized overhead. This paper introduces a universal parser and relational schema translator that can be utilized for all NCBI databases in Abstract Syntax Notation (ASN.1). The data models for OMIM, Entrez-Gene, Pubmed, MMDB and GenBank have been successfully converted into relational databases and all are easily linkable helping to answer complex biological questions. These tools facilitate research scientists to locally integrate databases from NCBI without significant workload or development time.

Neighboring Genes Show Correlated Evolution in Gene Expression

PubMed Central

Ghanbarian, Avazeh T.; Hurst, Laurence D.

2015-01-01

When considering the evolution of a gene’s expression profile, we commonly assume that this is unaffected by its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between neighboring genes in gene expression profiles in extant taxa. Indeed, in all eukaryotic genomes genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their expression or is gene expression evolution autonomous? To address this here we consider evolution of human gene expression since the human-chimp common ancestor, allowing for both variation in estimation of current expression level and error in Bayesian estimation of the ancestral state. We find that in all tissues and both sexes, the change in gene expression of a focal gene on average predicts the change in gene expression of neighbors. The effect is highly pronounced in the immediate vicinity (<100 kb) but extends much further. Sex-specific expression change is also genomically clustered. As genes increasing their expression in humans tend to avoid nuclear lamina domains and be enriched for the gene activator 5-hydroxymethylcytosine, we conclude that, most probably owing to chromatin level control of gene expression, a change in gene expression of one gene likely affects the expression evolution of neighbors, what we term expression piggybacking, an analog of hitchhiking. PMID:25743543

Mechanical stretching for tissue engineering: two-dimensional and three-dimensional constructs.

PubMed

Riehl, Brandon D; Park, Jae-Hong; Kwon, Il Keun; Lim, Jung Yul

2012-08-01

Mechanical cell stretching may be an attractive strategy for the tissue engineering of mechanically functional tissues. It has been demonstrated that cell growth and differentiation can be guided by cell stretch with minimal help from soluble factors and engineered tissues that are mechanically stretched in bioreactors may have superior organization, functionality, and strength compared with unstretched counterparts. This review explores recent studies on cell stretching in both two-dimensional (2D) and three-dimensional (3D) setups focusing on the applications of stretch stimulation as a tool for controlling cell orientation, growth, gene expression, lineage commitment, and differentiation and for achieving successful tissue engineering of mechanically functional tissues, including cardiac, muscle, vasculature, ligament, tendon, bone, and so on. Custom stretching devices and lab-specific mechanical bioreactors are described with a discussion on capabilities and limitations. While stretch mechanotransduction pathways have been examined using 2D stretch, studying such pathways in physiologically relevant 3D environments may be required to understand how cells direct tissue development under stretch. Cell stretch study using 3D milieus may also help to develop tissue-specific stretch regimens optimized with biochemical feedback, which once developed will provide optimal tissue engineering protocols.

Mechanical Stretching for Tissue Engineering: Two-Dimensional and Three-Dimensional Constructs

PubMed Central

Riehl, Brandon D.; Park, Jae-Hong; Kwon, Il Keun

2012-01-01

Mechanical cell stretching may be an attractive strategy for the tissue engineering of mechanically functional tissues. It has been demonstrated that cell growth and differentiation can be guided by cell stretch with minimal help from soluble factors and engineered tissues that are mechanically stretched in bioreactors may have superior organization, functionality, and strength compared with unstretched counterparts. This review explores recent studies on cell stretching in both two-dimensional (2D) and three-dimensional (3D) setups focusing on the applications of stretch stimulation as a tool for controlling cell orientation, growth, gene expression, lineage commitment, and differentiation and for achieving successful tissue engineering of mechanically functional tissues, including cardiac, muscle, vasculature, ligament, tendon, bone, and so on. Custom stretching devices and lab-specific mechanical bioreactors are described with a discussion on capabilities and limitations. While stretch mechanotransduction pathways have been examined using 2D stretch, studying such pathways in physiologically relevant 3D environments may be required to understand how cells direct tissue development under stretch. Cell stretch study using 3D milieus may also help to develop tissue-specific stretch regimens optimized with biochemical feedback, which once developed will provide optimal tissue engineering protocols. PMID:22335794

Identification of Human HK Genes and Gene Expression Regulation Study in Cancer from Transcriptomics Data Analysis

PubMed Central

Zhang, Zhang; Liu, Jingxing; Wu, Jiayan; Yu, Jun

2013-01-01

The regulation of gene expression is essential for eukaryotes, as it drives the processes of cellular differentiation and morphogenesis, leading to the creation of different cell types in multicellular organisms. RNA-Sequencing (RNA-Seq) provides researchers with a powerful toolbox for characterization and quantification of transcriptome. Many different human tissue/cell transcriptome datasets coming from RNA-Seq technology are available on public data resource. The fundamental issue here is how to develop an effective analysis method to estimate expression pattern similarities between different tumor tissues and their corresponding normal tissues. We define the gene expression pattern from three directions: 1) expression breadth, which reflects gene expression on/off status, and mainly concerns ubiquitously expressed genes; 2) low/high or constant/variable expression genes, based on gene expression level and variation; and 3) the regulation of gene expression at the gene structure level. The cluster analysis indicates that gene expression pattern is higher related to physiological condition rather than tissue spatial distance. Two sets of human housekeeping (HK) genes are defined according to cell/tissue types, respectively. To characterize the gene expression pattern in gene expression level and variation, we firstly apply improved K-means algorithm and a gene expression variance model. We find that cancer-associated HK genes (a HK gene is specific in cancer group, while not in normal group) are expressed higher and more variable in cancer condition than in normal condition. Cancer-associated HK genes prefer to AT-rich genes, and they are enriched in cell cycle regulation related functions and constitute some cancer signatures. The expression of large genes is also avoided in cancer group. These studies will help us understand which cell type-specific patterns of gene expression differ among different cell types, and particularly for cancer. PMID:23382867

Neighboring Genes Show Correlated Evolution in Gene Expression.

PubMed

Ghanbarian, Avazeh T; Hurst, Laurence D

2015-07-01

When considering the evolution of a gene's expression profile, we commonly assume that this is unaffected by its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between neighboring genes in gene expression profiles in extant taxa. Indeed, in all eukaryotic genomes genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their expression or is gene expression evolution autonomous? To address this here we consider evolution of human gene expression since the human-chimp common ancestor, allowing for both variation in estimation of current expression level and error in Bayesian estimation of the ancestral state. We find that in all tissues and both sexes, the change in gene expression of a focal gene on average predicts the change in gene expression of neighbors. The effect is highly pronounced in the immediate vicinity (<100 kb) but extends much further. Sex-specific expression change is also genomically clustered. As genes increasing their expression in humans tend to avoid nuclear lamina domains and be enriched for the gene activator 5-hydroxymethylcytosine, we conclude that, most probably owing to chromatin level control of gene expression, a change in gene expression of one gene likely affects the expression evolution of neighbors, what we term expression piggybacking, an analog of hitchhiking. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Pseudoislet formation enhances gene expression, insulin secretion and cytoprotective mechanisms of clonal human insulin-secreting 1.1B4 cells.

PubMed

Green, Alastair D; Vasu, Srividya; McClenaghan, Neville H; Flatt, Peter R

2015-10-01

We have studied the effects of cell communication on human beta cell function and resistance to cytotoxicity using the novel human insulin-secreting cell line 1.1B4 configured as monolayers and pseudoislets. Incubation with the incretin gut hormones GLP-1 and GIP caused dose-dependent stimulation of insulin secretion from 1.1B4 cell monolayers and pseudoislets. The secretory responses were 1.5-2.7-fold greater than monolayers. Cell viability (MTT), DNA damage (comet assay) and apoptosis (acridine orange/ethidium bromide staining) were investigated following 2-h exposure of 1.1B4 monolayers and pseudoislets to ninhydrin, H2O2, streptozotocin, glucose, palmitate or cocktails of proinflammatory cytokines. All agents tested decreased viability and increased DNA damage and apoptosis in both 1.1B4 monolayers and pseudoislets. However, pseudoislets exhibited significantly greater resistance to cytotoxicity (1.5-2.7-fold increases in LD50) and lower levels of DNA damage (1.3-3.4-fold differences in percentage tail DNA and olive tail moment) and apoptosis (1.3-1.5-fold difference) compared to monolayers. Measurement of gene expression by reverse-transcription, real-time PCR showed that genes involved with insulin secretion (INS, PDX1, PCSK1, PCSK2, GLP1R and GIPR), cell-cell communication (GJD2, GJA1 and CDH1) and antioxidant defence (SOD1, SOD2, GPX1 and CAT) were significantly upregulated in pseudoislets compared to monolayers, whilst the expression of proapoptotic genes (NOS2, MAPK8, MAPK10 and NFKB1) showed no significant differences. In summary, these data indicate cell-communication associated with three-dimensional islet architecture is important both for effective insulin secretion and for protection of human beta cells against cytotoxicity.

SYSTEMS BIOLOGY ANALYSES OF GENE EXPRESSION AND GENOME WIDE ASSOCIATION STUDY DATA IN OBSTRUCTIVE SLEEP APNEA

PubMed Central

LIU, YU; PATEL, SANJAY; NIBBE, ROD; MAXWELL, SEAN; CHOWDHURY, SALIM A.; KOYUTURK, MEHMET; ZHU, XIAOFENG; LARKIN, EMMA K.; BUXBAUM, SARAH G; PUNJABI, NARESH M.; GHARIB, SINA A.; REDLINE, SUSAN; CHANCE, MARK R.

2015-01-01

The precise molecular etiology of obstructive sleep apnea (OSA) is unknown; however recent research indicates that several interconnected aberrant pathways and molecular abnormalities are contributors to OSA. Identifying the genes and pathways associated with OSA can help to expand our understanding of the risk factors for the disease as well as provide new avenues for potential treatment. Towards these goals, we have integrated relevant high dimensional data from various sources, such as genome-wide expression data (microarray), protein-protein interaction (PPI) data and results from genome-wide association studies (GWAS) in order to define sub-network elements that connect some of the known pathways related to the disease as well as define novel regulatory modules related to OSA. Two distinct approaches are applied to identify sub-networks significantly associated with OSA. In the first case we used a biased approach based on sixty genes/proteins with known associations with sleep disorders and/or metabolic disease to seed a search using commercial software to discover networks associated with disease followed by information theoretic (mutual information) scoring of the sub-networks. In the second case we used an unbiased approach and generated an interactome constructed from publicly available gene expression profiles and PPI databases, followed by scoring of the network with p-values from GWAS data derived from OSA patients to uncover sub-networks significant for the disease phenotype. A comparison of the approaches reveals a number of proteins that have been previously known to be associated with OSA or sleep. In addition, our results indicate a novel association of Phosphoinositide 3-kinase, the STAT family of proteins and its related pathways with OSA. PMID:21121029

Integrated Left Ventricular Global Transcriptome and Proteome Profiling in Human End-Stage Dilated Cardiomyopathy.

PubMed

Colak, Dilek; Alaiya, Ayodele A; Kaya, Namik; Muiya, Nzioka P; AlHarazi, Olfat; Shinwari, Zakia; Andres, Editha; Dzimiri, Nduna

2016-01-01

The disease pathways leading to idiopathic dilated cardiomyopathy (DCM) are still elusive. The present study investigated integrated global transcriptional and translational changes in human DCM for disease biomarker discovery. We used identical myocardial tissues from five DCM hearts compared to five non-failing (NF) donor hearts for both transcriptome profiling using the ABI high-density oligonucleotide microarrays and proteome expression with One-Dimensional Nano Acquity liquid chromatography coupled with tandem mass spectrometry on the Synapt G2 system. We identified 1262 differentially expressed genes (DEGs) and 269 proteins (DEPs) between DCM cases and healthy controls. Among the most significantly upregulated (>5-fold) proteins were GRK5, APOA2, IGHG3, ANXA6, HSP90AA1, and ATP5C1 (p< 0.01). On the other hand, the most significantly downregulated proteins were GSTM5, COX17, CAV1 and ANXA3. At least ten entities were concomitantly upregulated on the two analysis platforms: GOT1, ALDH4A1, PDHB, BDH1, SLC2A11, HSP90AA1, HSP90AB1, H2AFV, HSPA5 and NDUFV1. Gene ontology analyses of DEGs and DEPs revealed significant overlap with enrichment of genes/proteins related to metabolic process, biosynthetic process, cellular component organization, oxidative phosphorylation, alterations in glycolysis and ATP synthesis, Alzheimer's disease, chemokine-mediated inflammation and cytokine signalling pathways. The concomitant use of transcriptome and proteome expression to evaluate global changes in DCM has led to the identification of sixteen commonly altered entities as well as novel genes, proteins and pathways whose cardiac functions have yet to be deciphered. This data should contribute towards better management of the disease.

Dynamic Control of Chromosome Topology and Gene Expression by a Chromatin Modification.

PubMed

Bian, Qian; Anderson, Erika C; Brejc, Katjuša; Meyer, Barbara J

2018-02-22

The function of chromatin modification in establishing higher-order chromosome structure during gene regulation has been elusive. We dissected the machinery and mechanism underlying the enrichment of histone modification H4K20me1 on hermaphrodite X chromosomes during Caenorhabditis elegans dosage compensation and discovered a key role for H4K20me1 in regulating X-chromosome topology and chromosome-wide gene expression. Structural and functional analysis of the dosage compensation complex (DCC) subunit DPY-21 revealed a novel Jumonji C demethylase subfamily that converts H4K20me2 to H4K20me1 in worms and mammals. Inactivation of demethylase activity in vivo by genome editing eliminated H4K20me1 enrichment on X chromosomes of somatic cells, increased X-linked gene expression, reduced X-chromosome compaction, and disrupted X-chromosome conformation by diminishing the formation of topologically associated domains. H4K20me1 is also enriched on the inactive X of female mice, making our studies directly relevant to mammalian development. Unexpectedly, DPY-21 also associates specifically with autosomes of nematode germ cells in a DCC-independent manner to enrich H4K20me1 and trigger chromosome compaction. Thus, DPY-21 is an adaptable chromatin regulator. Its H4K20me2 demethylase activity can be harnessed during development for distinct biological functions by targeting it to diverse genomic locations through different mechanisms. In both somatic cells and germ cells, H4K20me1 enrichment modulates three-dimensional chromosome architecture, demonstrating the direct link between chromatin modification and higher-order chromosome structure. © 2017 Bian et al.; Published by Cold Spring Harbor Laboratory Press.

Tumor Cell Plasticity in Uveal Melanoma

PubMed Central

Folberg, Robert; Arbieva, Zarema; Moses, Jonas; Hayee, Amin; Sandal, Tone; Kadkol, ShriHari; Lin, Amy Y.; Valyi-Nagy, Klara; Setty, Suman; Leach, Lu; Chévez-Barrios, Patricia; Larsen, Peter; Majumdar, Dibyen; Pe’er, Jacob; Maniotis, Andrew J.

2006-01-01

The histological detection of laminin-rich vasculogenic mimicry patterns in human primary uveal melanomas is associated with death from metastases. We therefore hypothesized that highly invasive uveal melanoma cells forming vasculogenic mimicry patterns after exposure to a laminin-rich three-dimensional microenvironment would differentially express genes associated with invasive and metastatic behavior. However, we discovered that genes associated with differentiation (GDF15 and ATF3) and suppression of proliferation (CDKNa1/p21) were up-regulated in highly invasive uveal melanoma cells forming vasculogenic mimicry patterns, and genes associated with promotion of invasive and metastatic behavior such as CD44, CCNE2 (cyclin E2), THBS1 (thrombospondin 1), and CSPG2 (chondroitin sulfate proteoglycan; versican) were down-regulated. After forming vasculogenic mimicry patterns, uveal melanoma cells invaded only short distances, failed to replicate, and changed morphologically from the invasive epithelioid to the indolent spindle A phenotype. In human tissue samples, uveal melanoma cells within vasculogenic mimicry patterns assumed the spindle A morphology, and the expression of Ki67 was significantly reduced in adjacent melanoma cells. Thus, the generation of vasculogenic mimicry patterns is accompanied by dampening of the invasive and metastatic uveal melanoma genotype and phenotype and underscores the plasticity of these cells in response to cues from the microenvironment. PMID:17003493

How large a training set is needed to develop a classifier for microarray data?

PubMed

Dobbin, Kevin K; Zhao, Yingdong; Simon, Richard M

2008-01-01

A common goal of gene expression microarray studies is the development of a classifier that can be used to divide patients into groups with different prognoses, or with different expected responses to a therapy. These types of classifiers are developed on a training set, which is the set of samples used to train a classifier. The question of how many samples are needed in the training set to produce a good classifier from high-dimensional microarray data is challenging. We present a model-based approach to determining the sample size required to adequately train a classifier. It is shown that sample size can be determined from three quantities: standardized fold change, class prevalence, and number of genes or features on the arrays. Numerous examples and important experimental design issues are discussed. The method is adapted to address ex post facto determination of whether the size of a training set used to develop a classifier was adequate. An interactive web site for performing the sample size calculations is provided. We showed that sample size calculations for classifier development from high-dimensional microarray data are feasible, discussed numerous important considerations, and presented examples.

Zebrafish Discoveries in Cancer Epigenetics.

PubMed

Chernyavskaya, Yelena; Kent, Brandon; Sadler, Kirsten C

2016-01-01

The cancer epigenome is fundamentally different than that of normal cells. How these differences arise in and contribute to carcinogenesis is not known, and studies using model organisms such as zebrafish provide an opportunity to address these important questions. Modifications of histones and DNA comprise the complex epigenome, and these influence chromatin structure, genome stability and gene expression, all of which are fundamental to the cellular changes that cause cancer. The cancer genome atlas covers the wide spectrum of genetic changes associated with nearly every cancer type, however, this catalog is currently uni-dimensional. As the pattern of epigenetic marks and chromatin structure in cancer cells is described and overlaid on the mutational landscape, the map of the cancer genome becomes multi-dimensional and highly complex. Two major questions remain in the field: (1) how the epigenome becomes repatterned in cancer and (2) which of these changes are cancer-causing. Zebrafish provide a tractable in vivo system to monitor the epigenome during transformation and to identify epigenetic drivers of cancer. In this chapter, we review principles of cancer epigenetics and discuss recent work using zebrafish whereby epigenetic modifiers were established as cancer driver genes, thus providing novel insights into the mechanisms of epigenetic reprogramming in cancer.

Incorporating biological information in sparse principal component analysis with application to genomic data.

PubMed

Li, Ziyi; Safo, Sandra E; Long, Qi

2017-07-11

Sparse principal component analysis (PCA) is a popular tool for dimensionality reduction, pattern recognition, and visualization of high dimensional data. It has been recognized that complex biological mechanisms occur through concerted relationships of multiple genes working in networks that are often represented by graphs. Recent work has shown that incorporating such biological information improves feature selection and prediction performance in regression analysis, but there has been limited work on extending this approach to PCA. In this article, we propose two new sparse PCA methods called Fused and Grouped sparse PCA that enable incorporation of prior biological information in variable selection. Our simulation studies suggest that, compared to existing sparse PCA methods, the proposed methods achieve higher sensitivity and specificity when the graph structure is correctly specified, and are fairly robust to misspecified graph structures. Application to a glioblastoma gene expression dataset identified pathways that are suggested in the literature to be related with glioblastoma. The proposed sparse PCA methods Fused and Grouped sparse PCA can effectively incorporate prior biological information in variable selection, leading to improved feature selection and more interpretable principal component loadings and potentially providing insights on molecular underpinnings of complex diseases.

A combinatorial approach towards the design of nanofibrous scaffolds for chondrogenesis

NASA Astrophysics Data System (ADS)

Ahmed, Maqsood; Ramos, Tiago André Da Silva; Damanik, Febriyani; Quang Le, Bach; Wieringa, Paul; Bennink, Martin; van Blitterswijk, Clemens; de Boer, Jan; Moroni, Lorenzo

2015-10-01

The extracellular matrix (ECM) is a three-dimensional (3D) structure composed of proteinaceous fibres that provide physical and biological cues to direct cell behaviour. Here, we build a library of hybrid collagen-polymer fibrous scaffolds with nanoscale dimensions and screen them for their ability to grow chondrocytes for cartilage repair. Poly(lactic acid) and poly (lactic-co-glycolic acid) at two different monomer ratios (85:15 and 50:50) were incrementally blended with collagen. Physical properties (wettability and stiffness) of the scaffolds were characterized and related to biological performance (proliferation, ECM production, and gene expression) and structure-function relationships were developed. We found that soft scaffolds with an intermediate wettability composed of the highly biodegradable PLGA50:50 and collagen, in two ratios (40:60 and 60:40), were optimal for chondrogenic differentiation of ATDC5 cells as determined by increased ECM production and enhanced cartilage specific gene expression. Long-term cultures indicated a stable phenotype with minimal de-differentiation or hypertrophy. The combinatorial methodology applied herein is a promising approach for the design and development of scaffolds for regenerative medicine.

Rank-based estimation in the {ell}1-regularized partly linear model for censored outcomes with application to integrated analyses of clinical predictors and gene expression data.

PubMed

Johnson, Brent A

2009-10-01

We consider estimation and variable selection in the partial linear model for censored data. The partial linear model for censored data is a direct extension of the accelerated failure time model, the latter of which is a very important alternative model to the proportional hazards model. We extend rank-based lasso-type estimators to a model that may contain nonlinear effects. Variable selection in such partial linear model has direct application to high-dimensional survival analyses that attempt to adjust for clinical predictors. In the microarray setting, previous methods can adjust for other clinical predictors by assuming that clinical and gene expression data enter the model linearly in the same fashion. Here, we select important variables after adjusting for prognostic clinical variables but the clinical effects are assumed nonlinear. Our estimator is based on stratification and can be extended naturally to account for multiple nonlinear effects. We illustrate the utility of our method through simulation studies and application to the Wisconsin prognostic breast cancer data set.

A combinatorial approach towards the design of nanofibrous scaffolds for chondrogenesis.

PubMed

Ahmed, Maqsood; Ramos, Tiago André da Silva; Damanik, Febriyani; Quang Le, Bach; Wieringa, Paul; Bennink, Martin; van Blitterswijk, Clemens; de Boer, Jan; Moroni, Lorenzo

2015-10-07

The extracellular matrix (ECM) is a three-dimensional (3D) structure composed of proteinaceous fibres that provide physical and biological cues to direct cell behaviour. Here, we build a library of hybrid collagen-polymer fibrous scaffolds with nanoscale dimensions and screen them for their ability to grow chondrocytes for cartilage repair. Poly(lactic acid) and poly (lactic-co-glycolic acid) at two different monomer ratios (85:15 and 50:50) were incrementally blended with collagen. Physical properties (wettability and stiffness) of the scaffolds were characterized and related to biological performance (proliferation, ECM production, and gene expression) and structure-function relationships were developed. We found that soft scaffolds with an intermediate wettability composed of the highly biodegradable PLGA50:50 and collagen, in two ratios (40:60 and 60:40), were optimal for chondrogenic differentiation of ATDC5 cells as determined by increased ECM production and enhanced cartilage specific gene expression. Long-term cultures indicated a stable phenotype with minimal de-differentiation or hypertrophy. The combinatorial methodology applied herein is a promising approach for the design and development of scaffolds for regenerative medicine.

Proteomics in medical microbiology.

PubMed

Cash, P

2000-04-01

The techniques of proteomics (high resolution two-dimensional electrophoresis and protein characterisation) are widely used for microbiological research to analyse global protein synthesis as an indicator of gene expression. The rapid progress in microbial proteomics has been achieved through the wide availability of whole genome sequences for a number of bacterial groups. Beyond providing a basic understanding of microbial gene expression, proteomics has also played a role in medical areas of microbiology. Progress has been made in the use of the techniques for investigating the epidemiology and taxonomy of human microbial pathogens, the identification of novel pathogenic mechanisms and the analysis of drug resistance. In each of these areas, proteomics has provided new insights that complement genomic-based investigations. This review describes the current progress in these research fields and highlights some of the technical challenges existing for the application of proteomics in medical microbiology. The latter concern the analysis of genetically heterogeneous bacterial populations and the integration of the proteomic and genomic data for these bacteria. The characterisation of the proteomes of bacterial pathogens growing in their natural hosts remains a future challenge.

Solution to a gene divergence problem under arbitrary stable nucleotide transition probabilities

NASA Technical Reports Server (NTRS)

Holmquist, R.

1976-01-01

A nucleic acid chain, L nucleotides in length, with the specific base sequence B(1)B(2) ... B(L) is defined by the L-dimensional vector B = (B(1), B(2), ..., B(L)). For twelve given constant non-negative transition probabilities that, in a specified position, the base B is replaced by the base B' in a single step, an exact analytical expression is derived for the probability that the position goes from base B to B' in X steps. Assuming that each base mutates independently of the others, an exact expression is derived for the probability that the initial gene sequence B goes to a sequence B' = (B'(1), B'(2), ..., B'(L)) after X = (X(1), X(2), ..., X(L)) base replacements. The resulting equations allow a more precise accounting for the effects of Darwinian natural selection in molecular evolution than does the idealized (biologically less accurate) assumption that each of the four nucleotides is equally likely to mutate to and be fixed as one of the other three. Illustrative applications of the theory to some problems of biological evolution are given.

3D spheroid cultures improve the metabolic gene expression profiles of HepaRG cells.

PubMed

Takahashi, Yu; Hori, Yuji; Yamamoto, Tomohisa; Urashima, Toshiki; Ohara, Yasunori; Tanaka, Hideo

2015-05-07

3D (three-dimensional) cultures are considered to be an effective method for toxicological studies; however, little evidence has been reported whether 3D cultures have an impact on hepatocellular physiology regarding lipid or glucose metabolism. In the present study, we conducted physiological characterization of hepatoma cell lines HepG2 and HepaRG cells cultured in 3D conditions using a hanging drop method to verify the effect of culture environment on cellular responses. Apo (Apolipoprotein)B as well as albumin secretion was augmented by 3D cultures. Expression of genes related to not only drug, but also glucose and lipid metabolism were significantly enhanced in 3D cultured HepaRG spheroids. Furthermore, mRNA levels of CYP (cytochrome P450) enzymes following exposure to corresponding inducers increased under the 3D condition. These data suggest that this simple 3D culture system without any special biomaterials can improve liver-specific characteristics including lipid metabolism. Considering that the system enables high-throughput assay, it may become a powerful tool for compound screening concerning hepatocellular responses in order to identify potential drugs. © 2015 Authors.

Influence of cartilage extracellular matrix molecules on cell phenotype and neocartilage formation.

PubMed

Grogan, Shawn P; Chen, Xian; Sovani, Sujata; Taniguchi, Noboru; Colwell, Clifford W; Lotz, Martin K; D'Lima, Darryl D

2014-01-01

Interaction between chondrocytes and the cartilage extracellular matrix (ECM) is essential for maintaining the cartilage's role as a low-friction and load-bearing tissue. In this study, we examined the influence of cartilage zone-specific ECM on human articular chondrocytes (HAC) in two-dimensional and three-dimensional (3D) environments. Two culture systems were used. SYSTEM 1: HAC were cultured on cell-culture plates that had been precoated with the following ECM molecules for 7 days: decorin, biglycan, tenascin C (superficial zone), collagen type II, hyaluronan (HA) (middle and deep zones), and osteopontin (deep zone). Uncoated standard culture plates were used as controls. Expanded cells were examined for phenotypic changes using real-time polymerase chain reaction. In addition, expanded cells were placed into high-density pellet cultures for 14 days. Neocartilage formation was assessed via gene expression and histology evaluations. SYSTEM 2: HAC that were cultured on untreated plates and encapsulated in a 3D alginate scaffold were mixed with one of the zone-specific ECM molecules. Cell viability, gene expression, and histology assessments were conducted on 14-day-old tissues. In HAC monolayer culture, exposure to decorin, HA, and osteopontin increased COL2A1 and aggrecan messenger RNA (mRNA) levels compared with controls. Biglycan up-regulated aggrecan without a significant impact on COL2A1 expression; Tenascin C reduced COL2A1 expression. Neocartilage formed after preculture on tenascin C and collagen type II expressed higher COL2A1 mRNA compared with control pellets. Preculture of HAC on HA decreased both COL2A1 and aggrecan expression levels compared with controls, which was consistent with histology. Reduced proteoglycan 4 (PRG4) mRNA levels were observed in HAC pellets that had been precultured with biglycan and collagen type II. Exposing HAC to HA directly in 3D-alginate culture most effectively induced neocartilage formation, showing increased COL2A1 and aggrecan, and reduced COL1A1 compared with controls. Decorin treatments increased HAC COL2A1 mRNA levels. These data indicate that an appropriate exposure to cartilage-specific ECM proteins could be used to enhance cartilage formation and to even induce the formation of zone-specific phenotypes to improve cartilage regeneration.

Building gene expression profile classifiers with a simple and efficient rejection option in R.

PubMed

Benso, Alfredo; Di Carlo, Stefano; Politano, Gianfranco; Savino, Alessandro; Hafeezurrehman, Hafeez

2011-01-01

The collection of gene expression profiles from DNA microarrays and their analysis with pattern recognition algorithms is a powerful technology applied to several biological problems. Common pattern recognition systems classify samples assigning them to a set of known classes. However, in a clinical diagnostics setup, novel and unknown classes (new pathologies) may appear and one must be able to reject those samples that do not fit the trained model. The problem of implementing a rejection option in a multi-class classifier has not been widely addressed in the statistical literature. Gene expression profiles represent a critical case study since they suffer from the curse of dimensionality problem that negatively reflects on the reliability of both traditional rejection models and also more recent approaches such as one-class classifiers. This paper presents a set of empirical decision rules that can be used to implement a rejection option in a set of multi-class classifiers widely used for the analysis of gene expression profiles. In particular, we focus on the classifiers implemented in the R Language and Environment for Statistical Computing (R for short in the remaining of this paper). The main contribution of the proposed rules is their simplicity, which enables an easy integration with available data analysis environments. Since in the definition of a rejection model tuning of the involved parameters is often a complex and delicate task, in this paper we exploit an evolutionary strategy to automate this process. This allows the final user to maximize the rejection accuracy with minimum manual intervention. This paper shows how the use of simple decision rules can be used to help the use of complex machine learning algorithms in real experimental setups. The proposed approach is almost completely automated and therefore a good candidate for being integrated in data analysis flows in labs where the machine learning expertise required to tune traditional classifiers might not be available.

Learning Parsimonious Classification Rules from Gene Expression Data Using Bayesian Networks with Local Structure.

PubMed

Lustgarten, Jonathan Lyle; Balasubramanian, Jeya Balaji; Visweswaran, Shyam; Gopalakrishnan, Vanathi

2017-03-01

The comprehensibility of good predictive models learned from high-dimensional gene expression data is attractive because it can lead to biomarker discovery. Several good classifiers provide comparable predictive performance but differ in their abilities to summarize the observed data. We extend a Bayesian Rule Learning (BRL-GSS) algorithm, previously shown to be a significantly better predictor than other classical approaches in this domain. It searches a space of Bayesian networks using a decision tree representation of its parameters with global constraints, and infers a set of IF-THEN rules. The number of parameters and therefore the number of rules are combinatorial to the number of predictor variables in the model. We relax these global constraints to a more generalizable local structure (BRL-LSS). BRL-LSS entails more parsimonious set of rules because it does not have to generate all combinatorial rules. The search space of local structures is much richer than the space of global structures. We design the BRL-LSS with the same worst-case time-complexity as BRL-GSS while exploring a richer and more complex model space. We measure predictive performance using Area Under the ROC curve (AUC) and Accuracy. We measure model parsimony performance by noting the average number of rules and variables needed to describe the observed data. We evaluate the predictive and parsimony performance of BRL-GSS, BRL-LSS and the state-of-the-art C4.5 decision tree algorithm, across 10-fold cross-validation using ten microarray gene-expression diagnostic datasets. In these experiments, we observe that BRL-LSS is similar to BRL-GSS in terms of predictive performance, while generating a much more parsimonious set of rules to explain the same observed data. BRL-LSS also needs fewer variables than C4.5 to explain the data with similar predictive performance. We also conduct a feasibility study to demonstrate the general applicability of our BRL methods on the newer RNA sequencing gene-expression data.

Condensin-Driven Remodeling of X-Chromosome Topology during Dosage Compensation

PubMed Central

Crane, Emily; Bian, Qian; McCord, Rachel Patton; Lajoie, Bryan R.; Wheeler, Bayly S.; Ralston, Edward J.; Uzawa, Satoru; Dekker, Job; Meyer, Barbara J.

2015-01-01

The three-dimensional organization of a genome plays a critical role in regulating gene expression, yet little is known about the machinery and mechanisms that determine higher-order chromosome structure1,2. Here we perform genome-wide chromosome conformation capture analysis, FISH, and RNA-seq to obtain comprehensive 3D maps of the Caenorhabditis elegans genome and to dissect X-chromosome dosage compensation, which balances gene expression between XX hermaphrodites and XO males. The dosage compensation complex (DCC), a condensin complex, binds to both hermaphrodite X chromosomes via sequence-specific recruitment elements on X (rex sites) to reduce chromosome-wide gene expression by half3–7. Most DCC condensin subunits also act in other condensin complexes to control the compaction and resolution of all mitotic and meiotic chromosomes5,6. By comparing chromosome structure in wild-type and DCC-defective embryos, we show that the DCC remodels hermaphrodite X chromosomes into a sex-specific spatial conformation distinct from autosomes. Dosage-compensated X chromosomes consist of self-interacting domains (~1 Mb) resembling mammalian Topologically Associating Domains (TADs)8,9. TADs on X have stronger boundaries and more regular spacing than on autosomes. Many TAD boundaries on X coincide with the highest-affinity rex sites and become diminished or lost in DCC-defective mutants, thereby converting the topology of X to a conformation resembling autosomes. rex sites engage in DCC-dependent long-range interactions, with the most frequent interactions occurring between rex sites at DCC-dependent TAD boundaries. These results imply that the DCC reshapes the topology of X by forming new TAD boundaries and reinforcing weak boundaries through interactions between its highest-affinity binding sites. As this model predicts, deletion of an endogenous rex site at a DCC-dependent TAD boundary using CRISPR/Cas9 greatly diminished the boundary. Thus, the DCC imposes a distinct higher-order structure onto X while regulating gene expression chromosome wide. PMID:26030525

Designing a Binding Interface for Control of Cancer Cell Adhesion via 3D Topography and Metabolic Oligosaccharide Engineering

PubMed Central

Du, Jian; Che, Pao-Lin; Wang, Zhi-Yun; Aich, Udayanath; Yarema, Kevin J.

2011-01-01

This study combines metabolic oligosaccharide engineering (MOE), a technology where the glycocalyx of living cells is endowed with chemical features not normally found in sugars, with custom-designed three dimensional biomaterial substrates to enhance the adhesion of cancer cells and control their morphology and gene expression. Specifically, Ac5ManNTGc, a thiol-bearing analogue of N-acetyl-d-mannosamine (ManNAc) was used to introduce thiolated sialic acids into the glycocalyx of human Jurkat T-lymphoma derived cells. In parallel 2D films and 3D electrospun nanofibrous scaffolds were prepared from polyethersulfone (PES) and (as controls) left unmodified or aminated. Alternately, the materials were malemided or gold-coated to provide bioorthogonal binding partners for the thiol groups newly expressed on the cell surface. Cell attachment was modulated by both the topography of the substrate surface and by the chemical compatibility of the binding interface between the cell and the substrate; a substantial increase in binding for normally non-adhesive Jurkat line for 3D scaffold compared to 2D surfaces with an added degree of adhesion resulting from chemoselective binding to malemidede-derivatived or gold-coated surfaces. In addition, the morphology of the cells attached to the 3D scaffolds via MOE-mediated adhesion was dramatically altered and the expression of genes involved in cell adhesion changed in a time-dependent manner. This study showed that cell adhesion could be enhanced, gene expression modulated, and cell fate controlled by introducing the 3D topograhical cues into the growth substrate and by creating a glycoengineered binding interface where the chemistry of both the cell surface and biomaterials scaffold was controlled to facilitate a new mode of carbohydrate-mediated adhesion. PMID:21549424

Human second trimester amniotic fluid cells are able to create embryoid body-like structures in vitro and to show typical expression profiles of embryonic and primordial germ cells.

PubMed

Antonucci, Ivana; Di Pietro, Roberta; Alfonsi, Melissa; Centurione, Maria Antonietta; Centurione, Lucia; Sancilio, Silvia; Pelagatti, Francesca; D'Amico, Maria Angela; Di Baldassarre, Angela; Piattelli, Adriano; Tetè, Stefano; Palka, Giandomenico; Borlongan, Cesar V; Stuppia, Liborio

2014-01-01

Human amniotic fluid-derived stem cells (AFSCs) represent a novel class of broadly multipotent stem cells sharing characteristics of both embryonic and adult stem cells. However, both the origin of these cells and their actual properties in terms of pluripotent differentiation potential are still debated. In order to verify the presence of features of pluripotency in human second trimester AFSCs, we have investigated the ability of these cells to form in vitro three-dimensional aggregates, known as embryoid bodies (EBs), and to express specific genes of embryonic stem cells (ESCs) and primordial germ cells (PGCs). EBs were obtained after 5 days of AFSC culture in suspension and showed positivity for alkaline phosphatase (AP) staining and for specific markers of pluripotency (OCT4 and SOX2). Moreover, EB-derived cells showed the expression of specific transcripts of the three germ layers. RT-PCR analysis, carried out at different culture times (second, third, fourth, fifth, and eighth passages), revealed the presence of specific markers of ESCs (such as FGF4 and DAPPA4), as well as of markers typical of PGCs and, in particular, genes involved in early stages of germ cell development (Fragilis, Stella, Vasa, c-Kit, Rnf17). Finally, the expression of genes related to the control of DNA methylation (DNMT3A, DNMT3b1, DNMT1, DNMT3L, MBD1, MBD2, MBD3, MDB4, MeCP2), as well as the lack of inactivation of the X-chromosome in female samples, was also demonstrated. Taken together, these data provide further evidence for the presence of common features among human AFSCs, PGCs, and ESCs.

A Bayesian Framework to Account for Complex Non-Genetic Factors in Gene Expression Levels Greatly Increases Power in eQTL Studies

PubMed Central

Durbin, Richard; Winn, John

2010-01-01

Gene expression measurements are influenced by a wide range of factors, such as the state of the cell, experimental conditions and variants in the sequence of regulatory regions. To understand the effect of a variable of interest, such as the genotype of a locus, it is important to account for variation that is due to confounding causes. Here, we present VBQTL, a probabilistic approach for mapping expression quantitative trait loci (eQTLs) that jointly models contributions from genotype as well as known and hidden confounding factors. VBQTL is implemented within an efficient and flexible inference framework, making it fast and tractable on large-scale problems. We compare the performance of VBQTL with alternative methods for dealing with confounding variability on eQTL mapping datasets from simulations, yeast, mouse, and human. Employing Bayesian complexity control and joint modelling is shown to result in more precise estimates of the contribution of different confounding factors resulting in additional associations to measured transcript levels compared to alternative approaches. We present a threefold larger collection of cis eQTLs than previously found in a whole-genome eQTL scan of an outbred human population. Altogether, 27% of the tested probes show a significant genetic association in cis, and we validate that the additional eQTLs are likely to be real by replicating them in different sets of individuals. Our method is the next step in the analysis of high-dimensional phenotype data, and its application has revealed insights into genetic regulation of gene expression by demonstrating more abundant cis-acting eQTLs in human than previously shown. Our software is freely available online at http://www.sanger.ac.uk/resources/software/peer/. PMID:20463871

Application of community phylogenetic approaches to understand gene expression: differential exploration of venom gene space in predatory marine gastropods.

PubMed

Chang, Dan; Duda, Thomas F

2014-06-05

Predatory marine gastropods of the genus Conus exhibit substantial variation in venom composition both within and among species. Apart from mechanisms associated with extensive turnover of gene families and rapid evolution of genes that encode venom components ('conotoxins'), the evolution of distinct conotoxin expression patterns is an additional source of variation that may drive interspecific differences in the utilization of species' 'venom gene space'. To determine the evolution of expression patterns of venom genes of Conus species, we evaluated the expression of A-superfamily conotoxin genes of a set of closely related Conus species by comparing recovered transcripts of A-superfamily genes that were previously identified from the genomes of these species. We modified community phylogenetics approaches to incorporate phylogenetic history and disparity of genes and their expression profiles to determine patterns of venom gene space utilization. Less than half of the A-superfamily gene repertoire of these species is expressed, and only a few orthologous genes are coexpressed among species. Species exhibit substantially distinct expression strategies, with some expressing sets of closely related loci ('under-dispersed' expression of available genes) while others express sets of more disparate genes ('over-dispersed' expression). In addition, expressed genes show higher dN/dS values than either unexpressed or ancestral genes; this implies that expression exposes genes to selection and facilitates rapid evolution of these genes. Few recent lineage-specific gene duplicates are expressed simultaneously, suggesting that expression divergence among redundant gene copies may be established shortly after gene duplication. Our study demonstrates that venom gene space is explored differentially by Conus species, a process that effectively permits the independent and rapid evolution of venoms in these species.

Critical high-dimensional state transitions in cell populations or why cancers follow the principle ``What does not kill me makes me stronger''

NASA Astrophysics Data System (ADS)

Huang, Sui

Transitions between high-dimensional attractor states in the quasi-potential landscape of the gene regulatory network, induced by environmental perturbations and/or facilitated by mutational rewiring of the network, underlie cell phenotype switching in development as well as in cancer progression, including acquisition of drug-resistant phenotypes. Considering heterogeneous cell populations as statistical ensembles of cells, and single-cell resolution gene expression profiling of cell populations undergoing a cell phenotype shift allow us now to map the topography of the landscape and its distortion. From snapshots of single-cell expression patterns of a cell population measured during major transitions we compute a quantity that identifies symmetry-breaking destabilization of attractors (bifurcation) and concomitant dimension-reduction of the state space manifold (landscape distortion) which precede critical transitions to new attractor states. The model predicts, and we show experimentally, the almost inevitable generation of aberrant cells associated with such critical transitions in multi-attractor landscapes: therapeutic perturbations which seek to push cancer cells to the apoptotic state, almost always produce ``rebellious'' cells which move in the ``opposite direction'': instead of dying they become more stem-cell-like and malignant. We show experimentally that the inadvertent generation of more malignant cancer cells by therapy indeed results from transition of surviving (but stressed) cells into unforeseen attractor states and not simply from selection of inherently more resistant cells. Thus, cancer cells follow not so much Darwin, as generally thought (survival of the fittest), but rather Nietzsche (What does not kill me makes me stronger). Supported by NIH (NCI, NIGMS), Alberta Innovates.

Bayesian feature selection for high-dimensional linear regression via the Ising approximation with applications to genomics.

PubMed

Fisher, Charles K; Mehta, Pankaj

2015-06-01

Feature selection, identifying a subset of variables that are relevant for predicting a response, is an important and challenging component of many methods in statistics and machine learning. Feature selection is especially difficult and computationally intensive when the number of variables approaches or exceeds the number of samples, as is often the case for many genomic datasets. Here, we introduce a new approach--the Bayesian Ising Approximation (BIA)-to rapidly calculate posterior probabilities for feature relevance in L2 penalized linear regression. In the regime where the regression problem is strongly regularized by the prior, we show that computing the marginal posterior probabilities for features is equivalent to computing the magnetizations of an Ising model with weak couplings. Using a mean field approximation, we show it is possible to rapidly compute the feature selection path described by the posterior probabilities as a function of the L2 penalty. We present simulations and analytical results illustrating the accuracy of the BIA on some simple regression problems. Finally, we demonstrate the applicability of the BIA to high-dimensional regression by analyzing a gene expression dataset with nearly 30 000 features. These results also highlight the impact of correlations between features on Bayesian feature selection. An implementation of the BIA in C++, along with data for reproducing our gene expression analyses, are freely available at http://physics.bu.edu/∼pankajm/BIACode. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Predicting biomedical metadata in CEDAR: A study of Gene Expression Omnibus (GEO).

PubMed

Panahiazar, Maryam; Dumontier, Michel; Gevaert, Olivier

2017-08-01

A crucial and limiting factor in data reuse is the lack of accurate, structured, and complete descriptions of data, known as metadata. Towards improving the quantity and quality of metadata, we propose a novel metadata prediction framework to learn associations from existing metadata that can be used to predict metadata values. We evaluate our framework in the context of experimental metadata from the Gene Expression Omnibus (GEO). We applied four rule mining algorithms to the most common structured metadata elements (sample type, molecular type, platform, label type and organism) from over 1.3million GEO records. We examined the quality of well supported rules from each algorithm and visualized the dependencies among metadata elements. Finally, we evaluated the performance of the algorithms in terms of accuracy, precision, recall, and F-measure. We found that PART is the best algorithm outperforming Apriori, Predictive Apriori, and Decision Table. All algorithms perform significantly better in predicting class values than the majority vote classifier. We found that the performance of the algorithms is related to the dimensionality of the GEO elements. The average performance of all algorithm increases due of the decreasing of dimensionality of the unique values of these elements (2697 platforms, 537 organisms, 454 labels, 9 molecules, and 5 types). Our work suggests that experimental metadata such as present in GEO can be accurately predicted using rule mining algorithms. Our work has implications for both prospective and retrospective augmentation of metadata quality, which are geared towards making data easier to find and reuse. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Down-regulate of Djrfc2 causes tissues hypertrophy during planarian regeneration.

PubMed

Guo, Qi; Zhao, Guixia; Ni, Jiajia; Guo, Yanan; Zhang, Yizhe; Tian, Qingnan; Zhang, Shoutao

2017-11-25

Planarians are an ideal model organism for regeneration research due to their amazing ability to regenerate. DNA replication is crucial for genome stability. Replication factor C (RFC), which is a replication factor C-like complex and plays an important role during DNA replication in eukaryotes, has been reported as a wound response factor during planarian regeneration. However, how RFC controls regeneration in planarians by regulating DNA replication remains to be explained. Here, we used a two-dimensional electrophoresis (2-DE) proteomic approach to identify differentially expressed proteins in intact and regenerated planarians. Approximately 132 protein spots showed differences between intact and regenerative tissues. We selected 21 significantly expressed protein spots and processed them using TOF MS analysis. Finally, we cloned three of these candidate genes (Djhsp70, Djrfc2, Djfaim), focusing on the function of Djrfc2 during regeneration. We found that the distribution of Djrfc2 tends toward the wound site. RNA interference (RNAi) of Djrfc2 increases the number of dividing cells and the expression level of planarian neoblast marker genes, which may result in hyper-proliferation. Our studies use an available approach to directly study the regeneration dynamic at the protein level and provide further evidence to support a function of Djrfc2 in planarian regeneration. Copyright © 2017. Published by Elsevier Inc.

Molecular evolution of multiple arylalkylamine N-acetyltransferase (AANAT) in fish.

PubMed

Zilberman-Peled, Bina; Bransburg-Zabary, Sharron; Klein, David C; Gothilf, Yoav

2011-01-01

Arylalkylamine N-acetyltransferase (AANAT) catalyzes the transfer of an acetyl group from acetyl coenzyme A (AcCoA) to arylalkylamines, including indolethylamines and phenylethylamines. Multiple aanats are present in teleost fish as a result of whole genome and gene duplications. Fish aanat1a and aanat2 paralogs display different patterns of tissue expression and encode proteins with different substrate preference: AANAT1a is expressed in the retina, and acetylates both indolethylamines and phenylethylamines; while AANAT2 is expressed in the pineal gland, and preferentially acetylates indolethylamines. The two enzymes are therefore thought to serve different roles. Here, the molecular changes that led to their specialization were studied by investigating the structure-function relationships of AANATs in the gilthead seabream (sb, Sperus aurata). Acetylation activity of reciprocal mutated enzymes pointed to specific residues that contribute to substrate specificity of the enzymes. Inhibition tests followed by complementary analyses of the predicted three-dimensional models of the enzymes, suggested that both phenylethylamines and indolethylamines bind to the catalytic pocket of both enzymes. These results suggest that substrate selectivity of AANAT1a and AANAT2 is determined by the positioning of the substrate within the catalytic pocket, and its accessibility to catalysis. This illustrates the evolutionary process by which enzymes encoded by duplicated genes acquire different activities and play different biological roles.

A study on Nim expression in Bacteroides fragilis

PubMed Central

Leitsch, David; Sóki, József; Kolarich, Daniel; Urbán, Edit; Nagy, Elisabeth

2016-01-01

Summary Members of the genus Bacteroides, mainly Bacteroides fragilis, can cause severe disease in man, especially after intestinal perforation in the course of abdominal surgery. Treatment is based on a small number of antibiotics, including metronidazole which has proved to be highly reliable throughout the last 40 to 50 years. Nevertheless, metronidazole resistance does occur in Bacteroides and has been mainly attributed to Nim proteins, a class of proteins with suggested nitroreductase function. Despite the potentially high importance of Nim proteins for human health, information on the expression of nim genes in Bacteroides fragilis is still lacking. It was the aim of this study to demonstrate expression of nim genes in B. fragilis at the protein level and, further, to correlate the level of Nim levels with the level of metronidazole resistance. By application of two-dimensional gel electrophoresis, Nim proteins could be readily identified in nim-positive strains but their levels were not elevated to a relevant extent after induction of resistance to high doses of metronidazole. Thus, the presented data do not provide evidence for Nim proteins acting as nitroreductases using metronidazole as a substrate because no correlation of Nim levels and level of resistance could be observed. Further, no evidence was found that Nim proteins protect B. fragilis from metronidazole by sequestering activated metronidazole. PMID:24448511

Integrative set enrichment testing for multiple omics platforms

PubMed Central

2011-01-01

Background Enrichment testing assesses the overall evidence of differential expression behavior of the elements within a defined set. When we have measured many molecular aspects, e.g. gene expression, metabolites, proteins, it is desirable to assess their differential tendencies jointly across platforms using an integrated set enrichment test. In this work we explore the properties of several methods for performing a combined enrichment test using gene expression and metabolomics as the motivating platforms. Results Using two simulation models we explored the properties of several enrichment methods including two novel methods: the logistic regression 2-degree of freedom Wald test and the 2-dimensional permutation p-value for the sum-of-squared statistics test. In relation to their univariate counterparts we find that the joint tests can improve our ability to detect results that are marginal univariately. We also find that joint tests improve the ranking of associated pathways compared to their univariate counterparts. However, there is a risk of Type I error inflation with some methods and self-contained methods lose specificity when the sets are not representative of underlying association. Conclusions In this work we show that consideration of data from multiple platforms, in conjunction with summarization via a priori pathway information, leads to increased power in detection of genomic associations with phenotypes. PMID:22118224

Redox-mediated enrichment of self-renewing adult human pancreatic cells that possess endocrine differentiation potential.

PubMed

Linning, Katrina D; Tai, Mei-Hui; Madhukar, Burra V; Chang, C C; Reed, Donald N; Ferber, Sarah; Trosko, James E; Olson, L Karl

2004-10-01

The limited availability of transplantable human islets has stimulated the development of methods needed to isolate adult pancreatic stem/progenitor cells capable of self-renewal and endocrine differentiation. The objective of this study was to determine whether modulation of intracellular redox state with N-acetyl-L-cysteine (NAC) would allow for the propagation of pancreatic stem/progenitor cells from adult human pancreatic tissue. Cells were propagated from human pancreatic tissue using a serum-free, low-calcium medium supplemented with NAC and tested for their ability to differentiate when cultured under different growth conditions. Human pancreatic cell (HPC) cultures coexpressed alpha-amylase, albumin, vimentin, and nestin. The HPC cultures, however, did not express other genes associated with differentiated pancreatic exocrine, duct, or endocrine cells. A number of transcription factors involved in endocrine cell development including Beta 2, Islet-1, Nkx6.1, Pax4, and Pax6 were expressed at variable levels in HPC cultures. In contrast, pancreatic duodenal homeobox factor 1 (Pdx-1) expression was extremely low and at times undetectable. Overexpression of Pdx-1 in HPC cultures stimulated somatostatin, glucagon, and carbonic anhydrase expression but had no effect on insulin gene expression. HPC cultures could form 3-dimensional islet-like cell aggregates, and this was associated with expression of somatostatin and glucagon but not insulin. Cultivation of HPCs in a differentiation medium supplemented with nicotinamide, exendin-4, and/or LY294002, an inhibitor of phosphatidylinositol-3 kinase, stimulated expression of insulin mRNA and protein. These data support the use of intracellular redox modulation for the enrichment of pancreatic stem/progenitor cells capable of self-renewal and endocrine differentiation.

Msn2p and Msn4p Control a Large Number of Genes Induced at the Diauxic Transition Which Are Repressed by Cyclic AMP in Saccharomyces cerevisiae

PubMed Central

Boy-Marcotte, Emmanuelle; Perrot, Michel; Bussereau, Françoise; Boucherie, Hélian; Jacquet, Michel

1998-01-01

The multicopy suppressors of the snf1 defect, Msn2p and Msn4p transcription factors (Msn2/4p), activate genes through the stress-responsive cis element (CCCCT) in response to various stresses. This cis element is also the target for repression by the cyclic AMP (cAMP)-signaling pathway. We analyzed the two-dimensional gel electrophoresis pattern of protein synthesis of the msn2 msn4 double mutant and compared it with that of the wild-type strain during exponential growth phase and at the diauxic transition. Thirty-nine gene products (including those of ALD3, GDH3, GLK1, GPP2, HSP104, HXK1, PGM2, SOD2, SSA3, SSA4, TKL2, TPS1, and YBR149W) are dependent upon Msn2/4p for their induction at the diauxic transition. The expression of all these genes is repressed by cAMP. Thirty other genes identified during this study are still inducible in the mutant. A subset of these genes were found to be superinduced at the diauxic transition, and others were subject to cAMP repression (including ACH1, ADH2, ALD6, ATP2, GPD1, ICL1, and KGD2). We conclude from this analysis that Msn2/4p control a large number of genes induced at the diauxic transition but that other, as-yet-uncharacterized regulators, also contribute to this response. In addition, we show here that cAMP repression applies to both Msn2/4p-dependent and -independent control of gene expression at the diauxic shift. Furthermore, the fact that all the Msn2/4p gene targets are subject to cAMP repression suggests that these regulators could be targets for the cAMP-signaling pathway. PMID:9495741

Regulation of Development and Nitrogen Fixation in Anabaena

DOE Office of Scientific and Technical Information (OSTI.GOV)

James W. Golden

2008-10-17

The regulation of development and cellular differentiation is important for all multicellular organisms. The nitrogen-fixing filamentous cyanobacterium Anabaena (also Nostoc) sp. PCC 7120 (hereafter Anabaena) provides a model of multicellular microbial development and pattern formation. Anabaena reduces N2 to ammonia in specialized terminally differentiated cells called heterocysts. A one-dimensional developmental pattern of single heterocysts regularly spaced along filaments of photosynthetic vegetative cells is established to form a multicellular organism composed of these two interdependent cell types. This multicellular growth pattern, the distinct phylogeny of cyanobacteria, and the suspected antiquity of heterocyst development make this an important model system. Our long-termmore » goal is to understand the regulatory network required for heterocyst development and nitrogen fixation. This project is focused on two key aspects of heterocyst regulation: one, the mechanism by which HetR controls the initiation of differentiation, and two, the cis and trans acting factors required for expression of the nitrogen-fixation (nif) genes. HetR is thought to be a central regulator of heterocyst development but the partners and mechanisms involved in this regulation are unknown. Our recent results indicate that PatS and other signals that regulate heterocyst pattern cannot interact, directly or indirectly, with a R223W mutant of HetR. We plan to use biochemical and genetic approaches to identify proteins that interact with the HetR protein, which will help reveal the mechanisms underlying its regulation of development. Our second goal is to determine how the nif genes are expressed. It is important to understand the mechanisms controlling nif genes since they represent the culmination of the differentiation process and the essence of heterocyst function. The Anabaena genome lacks the genes required for expression of nif genes present in other organisms such as rpoN (sigma 54) and nifA. We will use nifH-gfp reporter fusions to define the upstream sequences that are required for nifH expression and for genetic experiments to identify the trans-acting factors required for nifH regulation.« less

FARO server: Meta-analysis of gene expression by matching gene expression signatures to a compendium of public gene expression data.

PubMed

Manijak, Mieszko P; Nielsen, Henrik B

2011-06-11

Although, systematic analysis of gene annotation is a powerful tool for interpreting gene expression data, it sometimes is blurred by incomplete gene annotation, missing expression response of key genes and secondary gene expression responses. These shortcomings may be partially circumvented by instead matching gene expression signatures to signatures of other experiments. To facilitate this we present the Functional Association Response by Overlap (FARO) server, that match input signatures to a compendium of 242 gene expression signatures, extracted from more than 1700 Arabidopsis microarray experiments. Hereby we present a publicly available tool for robust characterization of Arabidopsis gene expression experiments which can point to similar experimental factors in other experiments. The server is available at http://www.cbs.dtu.dk/services/faro/.

The Spike-and-Slab Lasso Generalized Linear Models for Prediction and Associated Genes Detection.

PubMed

Tang, Zaixiang; Shen, Yueping; Zhang, Xinyan; Yi, Nengjun

2017-01-01

Large-scale "omics" data have been increasingly used as an important resource for prognostic prediction of diseases and detection of associated genes. However, there are considerable challenges in analyzing high-dimensional molecular data, including the large number of potential molecular predictors, limited number of samples, and small effect of each predictor. We propose new Bayesian hierarchical generalized linear models, called spike-and-slab lasso GLMs, for prognostic prediction and detection of associated genes using large-scale molecular data. The proposed model employs a spike-and-slab mixture double-exponential prior for coefficients that can induce weak shrinkage on large coefficients, and strong shrinkage on irrelevant coefficients. We have developed a fast and stable algorithm to fit large-scale hierarchal GLMs by incorporating expectation-maximization (EM) steps into the fast cyclic coordinate descent algorithm. The proposed approach integrates nice features of two popular methods, i.e., penalized lasso and Bayesian spike-and-slab variable selection. The performance of the proposed method is assessed via extensive simulation studies. The results show that the proposed approach can provide not only more accurate estimates of the parameters, but also better prediction. We demonstrate the proposed procedure on two cancer data sets: a well-known breast cancer data set consisting of 295 tumors, and expression data of 4919 genes; and the ovarian cancer data set from TCGA with 362 tumors, and expression data of 5336 genes. Our analyses show that the proposed procedure can generate powerful models for predicting outcomes and detecting associated genes. The methods have been implemented in a freely available R package BhGLM (http://www.ssg.uab.edu/bhglm/). Copyright © 2017 by the Genetics Society of America.

Establishment of Immortalized Primary Human Foreskin Keratinocytes and Their Application to Toxicity Assessment and Three Dimensional Skin Culture Construction.

PubMed

Choi, Moonju; Park, Minkyung; Lee, Suhyon; Lee, Jeong Woo; Cho, Min Chul; Noh, Minsoo; Lee, Choongho

2017-05-01

In spite of frequent usage of primary human foreskin keratinocytes (HFKs) in the study of skin biology, senescence-induced blockage of in vitro proliferation has been a big hurdle for their effective utilization. In order to overcome this passage limitation, we first isolated ten HFK lines from circumcision patients and successfully immortalized four of them via a retroviral transduction of high-risk human papillomavirus (HPV) E6 and E7 oncogenes. We confirmed expression of a keratinocyte marker protein, keratin 14 and two viral oncoproteins in these immortalized HFKs. We also observed their robust responsiveness to various exogenous stimuli, which was evidenced by increased mRNA expression of epithelial differentiation markers and pro-inflammatory genes in response to three reactive chemicals. In addition, their applicability to cytotoxicity assessment turned out to be comparable to that of HaCaT cells. Finally, we confirmed their differentiation capacity by construction of well-stratified three dimensional skin cultures. These newly established immortalized HFKs will be valuable tools not only for generation of in vitro skin disease models but also for prediction of potential toxicities of various cosmetic chemicals.

Establishment of Immortalized Primary Human Foreskin Keratinocytes and Their Application to Toxicity Assessment and Three Dimensional Skin Culture Construction

PubMed Central

Choi, Moonju; Park, Minkyung; Lee, Suhyon; Lee, Jeong Woo; Cho, Min Chul; Noh, Minsoo; Lee, Choongho

2017-01-01

In spite of frequent usage of primary human foreskin keratinocytes (HFKs) in the study of skin biology, senescence-induced blockage of in vitro proliferation has been a big hurdle for their effective utilization. In order to overcome this passage limitation, we first isolated ten HFK lines from circumcision patients and successfully immortalized four of them via a retroviral transduction of high-risk human papillomavirus (HPV) E6 and E7 oncogenes. We confirmed expression of a keratinocyte marker protein, keratin 14 and two viral oncoproteins in these immortalized HFKs. We also observed their robust responsiveness to various exogenous stimuli, which was evidenced by increased mRNA expression of epithelial differentiation markers and pro-inflammatory genes in response to three reactive chemicals. In addition, their applicability to cytotoxicity assessment turned out to be comparable to that of HaCaT cells. Finally, we confirmed their differentiation capacity by construction of well-stratified three dimensional skin cultures. These newly established immortalized HFKs will be valuable tools not only for generation of in vitro skin disease models but also for prediction of potential toxicities of various cosmetic chemicals. PMID:28365978

Hepatic esterase activity is increased in hepatocyte-like cells derived from human embryonic stem cells using a 3D culture system.

PubMed

Choi, Young-Jun; Kim, Hyemin; Kim, Ji-Woo; Yoon, Seokjoo; Park, Han-Jin

2018-05-01

The aim of the study is to generate a spherical three-dimensional (3D) aggregate of hepatocyte-like cells (HLCs) differentiated from human embryonic stem cells and to investigate the effect of the 3D environment on hepatic maturation and drug metabolism. Quantitative real-time PCR analysis indicated that gene expression of mature hepatocyte markers, drug-metabolizing enzymes, and hepatic transporters was significantly higher in HLCs cultured in the 3D system than in those cultured in a two-dimensional system (p < 0.001). Moreover, hepatocyte-specific functions, including albumin secretion and bile canaliculi formation, were increased in HLCs cultured in the 3D system. In particular, 3D spheroidal culture increased expression of CES1 and BCHE, which encode hepatic esterases (p < 0.001). The enhanced activities of these hepatic esterases were confirmed by the cholinesterase activity assay and the increased susceptibility of HLCs to oseltamivir, which is metabolized by CES1. 3D spheroidal culture enhances the maturation and drug metabolism of stem cell-derived HLCs, and this may help to optimize hepatic differentiation protocols for hepatotoxicity testing.

The quest for four-dimensional imaging in plant cell biology: it's just a matter of time

PubMed Central

Domozych, David S.

2012-01-01

Background Analysis of plant cell dynamics over time, or four-dimensional imaging (4-DI), represents a major goal of plant science. The ability to resolve structures in the third dimension within the cell or tissue during developmental events or in response to environmental or experimental stresses (i.e. 4-DI) is critical to our understanding of gene expression, post-expression modulations of macromolecules and sub-cellular system interactions. Scope Microscopy-based technologies have been profoundly integral to this type of investigation, and new and refined microscopy technologies now allow for the visualization of cell dynamics with unprecedented resolution, contrast and experimental versatility. However, certain realities of light and electron microscopy, choice of specimen and specimen preparation techniques limit the scope of readily attaining 4-DI. Today, the plant microscopist must use a combinatorial strategy whereby multiple microscopy-based investigations are used. Modern fluorescence, confocal laser scanning, transmission electron and scanning electron microscopy provide effective conduits for synthesizing data detailing live cell dynamics and highly resolved snapshots of specific cell structures that will ultimately lead to 4-DI. This review provides a synopsis of such technologies available. PMID:22628381

Digital gene expression analysis of the zebra finch genome

PubMed Central

2010-01-01

Background In order to understand patterns of adaptation and molecular evolution it is important to quantify both variation in gene expression and nucleotide sequence divergence. Gene expression profiling in non-model organisms has recently been facilitated by the advent of massively parallel sequencing technology. Here we investigate tissue specific gene expression patterns in the zebra finch (Taeniopygia guttata) with special emphasis on the genes of the major histocompatibility complex (MHC). Results Almost 2 million 454-sequencing reads from cDNA of six different tissues were assembled and analysed. A total of 11,793 zebra finch transcripts were represented in this EST data, indicating a transcriptome coverage of about 65%. There was a positive correlation between the tissue specificity of gene expression and non-synonymous to synonymous nucleotide substitution ratio of genes, suggesting that genes with a specialised function are evolving at a higher rate (or with less constraint) than genes with a more general function. In line with this, there was also a negative correlation between overall expression levels and expression specificity of contigs. We found evidence for expression of 10 different genes related to the MHC. MHC genes showed relatively tissue specific expression levels and were in general primarily expressed in spleen. Several MHC genes, including MHC class I also showed expression in brain. Furthermore, for all genes with highest levels of expression in spleen there was an overrepresentation of several gene ontology terms related to immune function. Conclusions Our study highlights the usefulness of next-generation sequence data for quantifying gene expression in the genome as a whole as well as in specific candidate genes. Overall, the data show predicted patterns of gene expression profiles and molecular evolution in the zebra finch genome. Expression of MHC genes in particular, corresponds well with expression patterns in other vertebrates. PMID:20359325

De novo mutations in the genome organizer CTCF cause intellectual disability.

PubMed

Gregor, Anne; Oti, Martin; Kouwenhoven, Evelyn N; Hoyer, Juliane; Sticht, Heinrich; Ekici, Arif B; Kjaergaard, Susanne; Rauch, Anita; Stunnenberg, Hendrik G; Uebe, Steffen; Vasileiou, Georgia; Reis, André; Zhou, Huiqing; Zweier, Christiane

2013-07-11

An increasing number of genes involved in chromatin structure and epigenetic regulation has been implicated in a variety of developmental disorders, often including intellectual disability. By trio exome sequencing and subsequent mutational screening we now identified two de novo frameshift mutations and one de novo missense mutation in CTCF in individuals with intellectual disability, microcephaly, and growth retardation. Furthermore, an individual with a larger deletion including CTCF was identified. CTCF (CCCTC-binding factor) is one of the most important chromatin organizers in vertebrates and is involved in various chromatin regulation processes such as higher order of chromatin organization, enhancer function, and maintenance of three-dimensional chromatin structure. Transcriptome analyses in all three individuals with point mutations revealed deregulation of genes involved in signal transduction and emphasized the role of CTCF in enhancer-driven expression of genes. Our findings indicate that haploinsufficiency of CTCF affects genomic interaction of enhancers and their regulated gene promoters that drive developmental processes and cognition. Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

A novel approach for human whole transcriptome analysis based on absolute gene expression of microarray data.

PubMed

Bikel, Shirley; Jacobo-Albavera, Leonor; Sánchez-Muñoz, Fausto; Cornejo-Granados, Fernanda; Canizales-Quinteros, Samuel; Soberón, Xavier; Sotelo-Mundo, Rogerio R; Del Río-Navarro, Blanca E; Mendoza-Vargas, Alfredo; Sánchez, Filiberto; Ochoa-Leyva, Adrian

2017-01-01

In spite of the emergence of RNA sequencing (RNA-seq), microarrays remain in widespread use for gene expression analysis in the clinic. There are over 767,000 RNA microarrays from human samples in public repositories, which are an invaluable resource for biomedical research and personalized medicine. The absolute gene expression analysis allows the transcriptome profiling of all expressed genes under a specific biological condition without the need of a reference sample. However, the background fluorescence represents a challenge to determine the absolute gene expression in microarrays. Given that the Y chromosome is absent in female subjects, we used it as a new approach for absolute gene expression analysis in which the fluorescence of the Y chromosome genes of female subjects was used as the background fluorescence for all the probes in the microarray. This fluorescence was used to establish an absolute gene expression threshold, allowing the differentiation between expressed and non-expressed genes in microarrays. We extracted the RNA from 16 children leukocyte samples (nine males and seven females, ages 6-10 years). An Affymetrix Gene Chip Human Gene 1.0 ST Array was carried out for each sample and the fluorescence of 124 genes of the Y chromosome was used to calculate the absolute gene expression threshold. After that, several expressed and non-expressed genes according to our absolute gene expression threshold were compared against the expression obtained using real-time quantitative polymerase chain reaction (RT-qPCR). From the 124 genes of the Y chromosome, three genes (DDX3Y, TXLNG2P and EIF1AY) that displayed significant differences between sexes were used to calculate the absolute gene expression threshold. Using this threshold, we selected 13 expressed and non-expressed genes and confirmed their expression level by RT-qPCR. Then, we selected the top 5% most expressed genes and found that several KEGG pathways were significantly enriched. Interestingly, these pathways were related to the typical functions of leukocytes cells, such as antigen processing and presentation and natural killer cell mediated cytotoxicity. We also applied this method to obtain the absolute gene expression threshold in already published microarray data of liver cells, where the top 5% expressed genes showed an enrichment of typical KEGG pathways for liver cells. Our results suggest that the three selected genes of the Y chromosome can be used to calculate an absolute gene expression threshold, allowing a transcriptome profiling of microarray data without the need of an additional reference experiment. Our approach based on the establishment of a threshold for absolute gene expression analysis will allow a new way to analyze thousands of microarrays from public databases. This allows the study of different human diseases without the need of having additional samples for relative expression experiments.

Unsupervised Bayesian linear unmixing of gene expression microarrays.

PubMed

Bazot, Cécile; Dobigeon, Nicolas; Tourneret, Jean-Yves; Zaas, Aimee K; Ginsburg, Geoffrey S; Hero, Alfred O

2013-03-19

This paper introduces a new constrained model and the corresponding algorithm, called unsupervised Bayesian linear unmixing (uBLU), to identify biological signatures from high dimensional assays like gene expression microarrays. The basis for uBLU is a Bayesian model for the data samples which are represented as an additive mixture of random positive gene signatures, called factors, with random positive mixing coefficients, called factor scores, that specify the relative contribution of each signature to a specific sample. The particularity of the proposed method is that uBLU constrains the factor loadings to be non-negative and the factor scores to be probability distributions over the factors. Furthermore, it also provides estimates of the number of factors. A Gibbs sampling strategy is adopted here to generate random samples according to the posterior distribution of the factors, factor scores, and number of factors. These samples are then used to estimate all the unknown parameters. Firstly, the proposed uBLU method is applied to several simulated datasets with known ground truth and compared with previous factor decomposition methods, such as principal component analysis (PCA), non negative matrix factorization (NMF), Bayesian factor regression modeling (BFRM), and the gradient-based algorithm for general matrix factorization (GB-GMF). Secondly, we illustrate the application of uBLU on a real time-evolving gene expression dataset from a recent viral challenge study in which individuals have been inoculated with influenza A/H3N2/Wisconsin. We show that the uBLU method significantly outperforms the other methods on the simulated and real data sets considered here. The results obtained on synthetic and real data illustrate the accuracy of the proposed uBLU method when compared to other factor decomposition methods from the literature (PCA, NMF, BFRM, and GB-GMF). The uBLU method identifies an inflammatory component closely associated with clinical symptom scores collected during the study. Using a constrained model allows recovery of all the inflammatory genes in a single factor.

Differential gene expression analysis in glioblastoma cells and normal human brain cells based on GEO database.

PubMed

Wang, Anping; Zhang, Guibin

2017-11-01

The differentially expressed genes between glioblastoma (GBM) cells and normal human brain cells were investigated to performed pathway analysis and protein interaction network analysis for the differentially expressed genes. GSE12657 and GSE42656 gene chips, which contain gene expression profile of GBM were obtained from Gene Expression Omniub (GEO) database of National Center for Biotechnology Information (NCBI). The 'limma' data packet in 'R' software was used to analyze the differentially expressed genes in the two gene chips, and gene integration was performed using 'RobustRankAggreg' package. Finally, pheatmap software was used for heatmap analysis and Cytoscape, DAVID, STRING and KOBAS were used for protein-protein interaction, Gene Ontology (GO) and KEGG analyses. As results: i) 702 differentially expressed genes were identified in GSE12657, among those genes, 548 were significantly upregulated and 154 were significantly downregulated (p<0.01, fold-change >1), and 1,854 differentially expressed genes were identified in GSE42656, among the genes, 1,068 were significantly upregulated and 786 were significantly downregulated (p<0.01, fold-change >1). A total of 167 differentially expressed genes including 100 upregulated genes and 67 downregulated genes were identified after gene integration, and the genes showed significantly different expression levels in GBM compared with normal human brain cells (p<0.05). ii) Interactions between the protein products of 101 differentially expressed genes were identified using STRING and expression network was established. A key gene, called CALM3, was identified by Cytoscape software. iii) GO enrichment analysis showed that differentially expressed genes were mainly enriched in 'neurotransmitter:sodium symporter activity' and 'neurotransmitter transporter activity', which can affect the activity of neurotransmitter transportation. KEGG pathway analysis showed that the differentially expressed genes were mainly enriched in 'protein processing in endoplasmic reticulum', which can affect protein processing in endoplasmic reticulum. The results showed that: i) 167 differentially expressed genes were identified from two gene chips after integration; and ii) protein interaction network was established, and GO and KEGG pathway analyses were successfully performed to identify and annotate the key gene, which provide new insights for the studies on GBN at gene level.

Discovery and validation of a glioblastoma co-expressed gene module

PubMed Central

Dunwoodie, Leland J.; Poehlman, William L.; Ficklin, Stephen P.; Feltus, Frank Alexander

2018-01-01

Tumors exhibit complex patterns of aberrant gene expression. Using a knowledge-independent, noise-reducing gene co-expression network construction software called KINC, we created multiple RNAseq-based gene co-expression networks relevant to brain and glioblastoma biology. In this report, we describe the discovery and validation of a glioblastoma-specific gene module that contains 22 co-expressed genes. The genes are upregulated in glioblastoma relative to normal brain and lower grade glioma samples; they are also hypo-methylated in glioblastoma relative to lower grade glioma tumors. Among the proneural, neural, mesenchymal, and classical glioblastoma subtypes, these genes are most-highly expressed in the mesenchymal subtype. Furthermore, high expression of these genes is associated with decreased survival across each glioblastoma subtype. These genes are of interest to glioblastoma biology and our gene interaction discovery and validation workflow can be used to discover and validate co-expressed gene modules derived from any co-expression network. PMID:29541392

Discovery and validation of a glioblastoma co-expressed gene module.

PubMed

Dunwoodie, Leland J; Poehlman, William L; Ficklin, Stephen P; Feltus, Frank Alexander

2018-02-16

Tumors exhibit complex patterns of aberrant gene expression. Using a knowledge-independent, noise-reducing gene co-expression network construction software called KINC, we created multiple RNAseq-based gene co-expression networks relevant to brain and glioblastoma biology. In this report, we describe the discovery and validation of a glioblastoma-specific gene module that contains 22 co-expressed genes. The genes are upregulated in glioblastoma relative to normal brain and lower grade glioma samples; they are also hypo-methylated in glioblastoma relative to lower grade glioma tumors. Among the proneural, neural, mesenchymal, and classical glioblastoma subtypes, these genes are most-highly expressed in the mesenchymal subtype. Furthermore, high expression of these genes is associated with decreased survival across each glioblastoma subtype. These genes are of interest to glioblastoma biology and our gene interaction discovery and validation workflow can be used to discover and validate co-expressed gene modules derived from any co-expression network.

Feature Augmentation via Nonparametrics and Selection (FANS) in High-Dimensional Classification.

PubMed

Fan, Jianqing; Feng, Yang; Jiang, Jiancheng; Tong, Xin

We propose a high dimensional classification method that involves nonparametric feature augmentation. Knowing that marginal density ratios are the most powerful univariate classifiers, we use the ratio estimates to transform the original feature measurements. Subsequently, penalized logistic regression is invoked, taking as input the newly transformed or augmented features. This procedure trains models equipped with local complexity and global simplicity, thereby avoiding the curse of dimensionality while creating a flexible nonlinear decision boundary. The resulting method is called Feature Augmentation via Nonparametrics and Selection (FANS). We motivate FANS by generalizing the Naive Bayes model, writing the log ratio of joint densities as a linear combination of those of marginal densities. It is related to generalized additive models, but has better interpretability and computability. Risk bounds are developed for FANS. In numerical analysis, FANS is compared with competing methods, so as to provide a guideline on its best application domain. Real data analysis demonstrates that FANS performs very competitively on benchmark email spam and gene expression data sets. Moreover, FANS is implemented by an extremely fast algorithm through parallel computing.

Feature Augmentation via Nonparametrics and Selection (FANS) in High-Dimensional Classification

PubMed Central

Feng, Yang; Jiang, Jiancheng; Tong, Xin

2015-01-01

We propose a high dimensional classification method that involves nonparametric feature augmentation. Knowing that marginal density ratios are the most powerful univariate classifiers, we use the ratio estimates to transform the original feature measurements. Subsequently, penalized logistic regression is invoked, taking as input the newly transformed or augmented features. This procedure trains models equipped with local complexity and global simplicity, thereby avoiding the curse of dimensionality while creating a flexible nonlinear decision boundary. The resulting method is called Feature Augmentation via Nonparametrics and Selection (FANS). We motivate FANS by generalizing the Naive Bayes model, writing the log ratio of joint densities as a linear combination of those of marginal densities. It is related to generalized additive models, but has better interpretability and computability. Risk bounds are developed for FANS. In numerical analysis, FANS is compared with competing methods, so as to provide a guideline on its best application domain. Real data analysis demonstrates that FANS performs very competitively on benchmark email spam and gene expression data sets. Moreover, FANS is implemented by an extremely fast algorithm through parallel computing. PMID:27185970

GPU-powered Shotgun Stochastic Search for Dirichlet process mixtures of Gaussian Graphical Models

PubMed Central

Mukherjee, Chiranjit; Rodriguez, Abel

2016-01-01

Gaussian graphical models are popular for modeling high-dimensional multivariate data with sparse conditional dependencies. A mixture of Gaussian graphical models extends this model to the more realistic scenario where observations come from a heterogenous population composed of a small number of homogeneous sub-groups. In this paper we present a novel stochastic search algorithm for finding the posterior mode of high-dimensional Dirichlet process mixtures of decomposable Gaussian graphical models. Further, we investigate how to harness the massive thread-parallelization capabilities of graphical processing units to accelerate computation. The computational advantages of our algorithms are demonstrated with various simulated data examples in which we compare our stochastic search with a Markov chain Monte Carlo algorithm in moderate dimensional data examples. These experiments show that our stochastic search largely outperforms the Markov chain Monte Carlo algorithm in terms of computing-times and in terms of the quality of the posterior mode discovered. Finally, we analyze a gene expression dataset in which Markov chain Monte Carlo algorithms are too slow to be practically useful. PMID:28626348

GPU-powered Shotgun Stochastic Search for Dirichlet process mixtures of Gaussian Graphical Models.

PubMed

Mukherjee, Chiranjit; Rodriguez, Abel

2016-01-01

Gaussian graphical models are popular for modeling high-dimensional multivariate data with sparse conditional dependencies. A mixture of Gaussian graphical models extends this model to the more realistic scenario where observations come from a heterogenous population composed of a small number of homogeneous sub-groups. In this paper we present a novel stochastic search algorithm for finding the posterior mode of high-dimensional Dirichlet process mixtures of decomposable Gaussian graphical models. Further, we investigate how to harness the massive thread-parallelization capabilities of graphical processing units to accelerate computation. The computational advantages of our algorithms are demonstrated with various simulated data examples in which we compare our stochastic search with a Markov chain Monte Carlo algorithm in moderate dimensional data examples. These experiments show that our stochastic search largely outperforms the Markov chain Monte Carlo algorithm in terms of computing-times and in terms of the quality of the posterior mode discovered. Finally, we analyze a gene expression dataset in which Markov chain Monte Carlo algorithms are too slow to be practically useful.

NATbox: a network analysis toolbox in R.

PubMed

Chavan, Shweta S; Bauer, Michael A; Scutari, Marco; Nagarajan, Radhakrishnan

2009-10-08

There has been recent interest in capturing the functional relationships (FRs) from high-throughput assays using suitable computational techniques. FRs elucidate the working of genes in concert as a system as opposed to independent entities hence may provide preliminary insights into biological pathways and signalling mechanisms. Bayesian structure learning (BSL) techniques and its extensions have been used successfully for modelling FRs from expression profiles. Such techniques are especially useful in discovering undocumented FRs, investigating non-canonical signalling mechanisms and cross-talk between pathways. The objective of the present study is to develop a graphical user interface (GUI), NATbox: Network Analysis Toolbox in the language R that houses a battery of BSL algorithms in conjunction with suitable statistical tools for modelling FRs in the form of acyclic networks from gene expression profiles and their subsequent analysis. NATbox is a menu-driven open-source GUI implemented in the R statistical language for modelling and analysis of FRs from gene expression profiles. It provides options to (i) impute missing observations in the given data (ii) model FRs and network structure from gene expression profiles using a battery of BSL algorithms and identify robust dependencies using a bootstrap procedure, (iii) present the FRs in the form of acyclic graphs for visualization and investigate its topological properties using network analysis metrics, (iv) retrieve FRs of interest from published literature. Subsequently, use these FRs as structural priors in BSL (v) enhance scalability of BSL across high-dimensional data by parallelizing the bootstrap routines. NATbox provides a menu-driven GUI for modelling and analysis of FRs from gene expression profiles. By incorporating readily available functions from existing R-packages, it minimizes redundancy and improves reproducibility, transparency and sustainability, characteristic of open-source environments. NATbox is especially suited for interdisciplinary researchers and biologists with minimal programming experience and would like to use systems biology approaches without delving into the algorithmic aspects. The GUI provides appropriate parameter recommendations for the various menu options including default parameter choices for the user. NATbox can also prove to be a useful demonstration and teaching tool in graduate and undergraduate course in systems biology. It has been tested successfully under Windows and Linux operating systems. The source code along with installation instructions and accompanying tutorial can be found at http://bioinformatics.ualr.edu/natboxWiki/index.php/Main_Page.

Comprehensive discovery of subsample gene expression components by information explanation: therapeutic implications in cancer.

PubMed

Pepke, Shirley; Ver Steeg, Greg

2017-03-15

De novo inference of clinically relevant gene function relationships from tumor RNA-seq remains a challenging task. Current methods typically either partition patient samples into a few subtypes or rely upon analysis of pairwise gene correlations that will miss some groups in noisy data. Leveraging higher dimensional information can be expected to increase the power to discern targetable pathways, but this is commonly thought to be an intractable computational problem. In this work we adapt a recently developed machine learning algorithm for sensitive detection of complex gene relationships. The algorithm, CorEx, efficiently optimizes over multivariate mutual information and can be iteratively applied to generate a hierarchy of relatively independent latent factors. The learned latent factors are used to stratify patients for survival analysis with respect to both single factors and combinations. These analyses are performed and interpreted in the context of biological function annotations and protein network interactions that might be utilized to match patients to multiple therapies. Analysis of ovarian tumor RNA-seq samples demonstrates the algorithm's power to infer well over one hundred biologically interpretable gene cohorts, several times more than standard methods such as hierarchical clustering and k-means. The CorEx factor hierarchy is also informative, with related but distinct gene clusters grouped by upper nodes. Some latent factors correlate with patient survival, including one for a pathway connected with the epithelial-mesenchymal transition in breast cancer that is regulated by a microRNA that modulates epigenetics. Further, combinations of factors lead to a synergistic survival advantage in some cases. In contrast to studies that attempt to partition patients into a small number of subtypes (typically 4 or fewer) for treatment purposes, our approach utilizes subgroup information for combinatoric transcriptional phenotyping. Considering only the 66 gene expression groups that are found to both have significant Gene Ontology enrichment and are small enough to indicate specific drug targets implies a computational phenotype for ovarian cancer that allows for 3 66 possible patient profiles, enabling truly personalized treatment. The findings here demonstrate a new technique that sheds light on the complexity of gene expression dependencies in tumors and could eventually enable the use of patient RNA-seq profiles for selection of personalized and effective cancer treatments.